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1 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 2
JOURNAL OF REGIONAL SOCIO-
ECONOMIC ISSUES (JRSEI)
Volume 10, Issue 3, September 2020
Journal of Regional & Socio-Economic Issues (Print) ISSN 2049-1395
Journal of Regional & Socio-Economic Issues (Online) ISSN 2049-1409
Indexed by Copernicus Index, DOAJ (Director of Open Access Journal), EBSCO, Cabell’s Index
The journal is catalogued in the following catalogues: ROAD: Directory of Open Access Scholarly
Resources, OCLC WorldCat, EconBiz - ECONIS, CITEFACTOR, OpenAccess
3 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
JOURNAL OF REGIONAL
SOCIO-ECONOMIC ISSUES (JRSEI) ISSN No. 2049-1409
Aims of the Journal: Journal of Regional Socio-Economic Issues (JRSEI) is an international
multidisciplinary refereed journal the purpose of which is to present papers manuscripts linked
to all aspects of regional socio-economic and business and related issues. The views expressed
in this journal are the personal views of the authors and do not necessarily reflect the views of
JRSEI journal. The journal invites contributions from both academic and industry scholars.
Electronic submissions are highly encouraged (mail to: [email protected]).
Indexed by Copernicus Index, DOAJ (Director of Open Access Journal), EBSCO, Cabell’s Index
International Institute of Organized Research (I2OR) database
The journal is catalogued in the following catalogues: ROAD: Directory of Open Access Scholarly
Resources, OCLC WorldCat, EconBiz - ECONIS, CITEFACTOR, OpenAccess
Chief-Editor Prof. Dr. George M. Korres: University of the Aegean, Department of Geography,
Editorial Board (alphabetical order) Assoc. Prof. Dr. Zacharoula S. Andreopoulou, Aristotle University of
Thessaloniki, Faculty of Forestry and Natural Environment, School of
Agriculture, Forestry & Natural Environment, [email protected]
Dr. Stilianos Alexiadis, Ministry of Reconstruction of Production, Environment
& Energy Department of Strategic Planning, Rural Development, Evaluation &
& Statistics, [email protected]; [email protected]
Prof. Dr. Maria Athina Artavani, Department of Military Science,
Hellenic Military Academy, Greece, [email protected]
Prof. Dr. Elias G. Carayannis: School of Business, George Washington University,
USA, [email protected]; [email protected]
Emeritus Prof. Dr. Christos Frangos, University of West Attica, Athens,
Emeritus Prof. Dr. Andreas Demetriou, Department of Military Science,
Hellenic Military Academy, Greece, [email protected] Ass. Professor Dr Vicky Delitheou, Department of Economics and Regional
Development, Panteion University of Social and Political Sciences of Athens,
Email: [email protected]
Prof. Dr. Hanna Dudek: Warsaw University of Life Sciences, [email protected]
Prof. Dr. George Gkantzias: Hellenic Open University, [email protected]
Prof. Dr. George Halkos, Department of Economics, University of Thessaly,
Prof. Dr. Richard Harris: Durham University, [email protected]
Assoc. Prof. Dr. Olga-Ioanna Kalantzi, Department of Environment, University
of the Aegean, Email: [email protected]
Prof. Dr. Stephanos Karagiannis, Panteion University, [email protected]
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 4
Ass. Prof. Dr. Marina-Selini Katsaiti, Department of Economics & Finance, College of
Business & Economics, United Arab Emirates University, UAE,
Emeritus Prof. Dr. Christos Kitsos, University of West Attica, [email protected]
Assoc. Prof. Dr. Aikaterini Kokkinou, Department of Military Science, Hellenic
Military Academy, Greece, [email protected]
Prof. Dr. Elias A. Kourliouros, Department of Economics, University of Patras,
[email protected]; [email protected]
Emeritus Prof. Dr. Dimitrios Lagos, Department of Business Administration, University
of the Aegean, [email protected]
Assoc. Prof. Dr. Charalambos Louca: Head of Business Department, Director of
Research Department, [email protected]
Prof. Dr. Evangelos Manolas, Department of Forestry & Management of the
Environment & Natural Resources, School of Agricultural & Forestry Sciences,
Democritus University of Thrace, [email protected]
Prof. Dr. Emmanuel Marmaras†: Technical University of Crete
Prof. Dr. Ioannis Th. Mazis, National and Kapodistrian University of Athens,
Faculty of Turkish Studies and Modern Asian Studies,
School of Economics and Political Sciences, [email protected];
Prof. Dr. Maria Michailidis: Department of Management & MIS, University of Nicosia,
Prof. Dr. Photis Nanopoulos, Former Director of Eurostat, [email protected]
Prof. Dr. Nikitas Nikitakos, Department of Shipping Trade and Transport, University of
the Aegean, Email: [email protected]
Dr. Pablo Ruiz-Nápoles, Faculty of Economics, Universidad Nacional
Autonoma de Mexico, [email protected]
Assistant Professor Dr. Efstratios Papanis, Department of Sociology, University of the
Aegean, [email protected]
Assoc. Prof. Gerasimos Pavlogeorgatos (PhD), Department of Cultural Technology and
Communication, University of the Aegean, [email protected]
Prof. Dr. George Polychronopoulos, Professor, Member of the Board of Trustees,
University of West Attica, [email protected]
Prof. Dr. Kiran Prasad, Professor Sri Padmavati Mahila University
[email protected]; [email protected];
Dr. Efthymia Sarantakou, Architect Engineer, adjunct lecturer at the Hellenic Open
University & at Technological Educational Institute of Athens, [email protected]
Professor Yevhen Savelyev, Vice-Rector, Ternopil National Economic
University, Ukraine,[email protected];
Prof. Dr. Anastasia Stratigea, National Technical University of Athens, School of Rural
& Surveying Engineering, Deparment of Geography & Regional Planning,
Prof. Paris Tsartas, Harokopeio University, Athens, Greece, [email protected]
Prof. Dr. George O. Tsobanoglou, University of the Aegean, Department of Sociology,
Professor Dr. George Tsourvakas, School of Economic and Political Studies,
Department of Journalism and Mass Communications, Aristotle University of
Thessaloniki, [email protected]
Prof. Dr. George Zestos, Christopher Newport University, [email protected]
5 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table of Contents
Editorial Board 3
Table of Contents 5
Paper 1: Employment, education and vocational training in Greece: Micro-
level analysis and interaction effects, (by Stavros Rodokanakis) 6-21
6
Paper 2: Community Involvement in event planning: Cases from Greek
Festival Market (by Sofoklis Skoultsos and Alexios- Patapios Kontis) 22-35
22
Paper 3: Employee training in Athens luxury hotels and its relation to job
efficiency and company loyalty (by Papageorgiou Athina, Kikilia Ekaterini
and Varelas Sotirios) 36-45
Paper 4: Sharing economy in time of economic crisis: The owners'
perspective of Airbnb rentals in Greek cities (by Sofoklis Skoultsos, Anna
Kyriakaki, Alexios – Patapios Kontis, and Despina Sdrali) 46-62
Paper 5: The Challenge of Spatial Information Accessibility for Agricultural
Policies: Case of Pakistan (by Asmat Ali and Muhammad Imran) 63-101
36
46
62
Paper 6: Assessing the Reform Options of the Public Pension Scheme of the
Republic of Cyprus (by Charalambos N. Louca, George M. Korres and
George O. Tsobanoglou) 102-132
102
Paper 7: The Royal City Andrapolis of «The Acts of Thomas» (by Alex
Kordosis) 133-136
133
Call for Papers 137
Instructions to Authors
138
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 6
Employment, education and vocational training in Greece: Micro-level
analysis and interaction effects
Abstract:
This article examines the impact that level of education and vocational training had on the
Greek labour market, and especially on the chances of finding a job, during the period 1988-
2000, and tests human capital theory and matching theory following an extended interaction
effects analysis. It is not asserted categorically here that the mismatch between supply and
demand for labour in Greece was due to training mismatch alone, but it is contended that this
should be seriously considered as one of the reasons for the unemployment problem in
Greece, at least for the period prior to the current crisis.
Keywords: J08 Labor Economics Policies; J24 Human Capital; Skills; D04 Microeconomic
Policy: Formulation, Implementation, and Evaluation; C54 Quantitative Policy Modeling;
I280 Education: Government Policy.
Stavros Rodokanakis1
1 Corresponding-Address: Dr Stavros Rodokanakis (Visiting Fellow), Department of Social and Policy Sciences,
University of Bath, Claverton Down, Bath BA2 7AY, England. E-mail: [email protected]
7 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Research Questions and Methodology
Since the early 1990s, there was a shift from ‘passive’ to active labour market policies
(ALMPs) in European countries. In the case of Greece, it is questionable whether vocational
training from the end of the 1980s onwards was accompanied by any real improvement in
matching supply with demand or increasing people’s chances of finding a job.
In particular, the human capital theory is tested, as well as the matching theory. What
has become clear is that the EU approach to vocational training has been very much
influenced by the human capital theory. The matching theory is also considered, because in
contrast to the human capital view under this perspective too much education leads to a lack
of training and consequently, an over-educated often unemployable workforce, which
appears to be the case in Greece and other Southern European countries (Liagouras et al.,
2003; Tsakloglou and Cholezas, 2005; Dolton and Marcenaro-Gutierrez, 2009; Thomaidou
et al., 2009; Karamessini, 2010). The key research question of the paper is what was the
impact of EU funded vocational training on the Greek labour market and individual job
seekers who undertook this training from 1988 to 2000?
At the micro-level, whether the vocational training courses and educational level
increased the chances of finding a job at the participant level is examined econometrically.
The research will determine whether or not the programmes did help the unemployed to get
any work and addresses the following question, namely ‘What was the impact of the
training programmes at the participant level?’. This question was operationalized by
empirically testing the following sub-questions:
• Did the social and demographic characteristics of an individual in Greece affect the
probability of finding employment during the period under investigation?
• Did the introduction of training courses funded by the EU have a statistically significant
effect on the probability of finding employment?
• Did university graduates in Greece face greater difficulties in finding a job compared to
those less educated (as relevant literature and aggregate statistics have suggested - see
Meghir et al., 1989; OECD, 1990; Eurostat: Education and Employment Prospects, 1995;
Iliades, 1995; IN.E./GSEE-ADEDY, 1999; Katsikas, 2005)?
2. Micro-Level of Analysis I: Theoetical Approaches
2.1 Training as human capital and the matching theory
The theory of human capital (Becker, 1964; Ben-Porath, 1967; Mincer 1974) has been
criticized for not being able to explain comprehensively the functions of vocational training,
for it merely considers it as an investment (Papakonstantinou, 1998). There has also been a
considerable amount of empirical research on the closely related topics of education and
skills, including Prais (1995) and Murray and Steedman (1998); closely related to the
current research is study on the increasing role of skilled labour in the economy (Berman et
al., 1994; Machin and van Reenen, 1998).
By contrast, the advocates of matching theory claim that under-education will result
in an increased necessity for more training. However, it is not yet clear whether training can
make up for inadequacies in formal education (substitution) or if it can just add to variations
in human capital (complementarity) that are already present. It could be the case that it is
only the features of the job (level and kind of job) in which the substitution aspects of
training are to be found, and that it is only in those aspects of formal education (level and
breadth) that the complementarity nature of training is obvious (van Smoorenburg and van
der Velden, 2000).
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 8
2.2 Literature review on the impact of training at the micro-level
The findings show that the more expensive programmes with a significant amount of
training appear to have been the most effective at increasing employment prospects (see
Brodaty et al., 2001; van Ours, 2001; Kluve and Schmidt, 2002; Raaum and Torp, 2002;
Kluve et al., 2005). However, national studies during the early to mid-2000s did not find
positive impacts of training on employment (Gerfin and Lechner, 2000; Regner, 2002).
Other studies that found mixed effects of participation in training programmes on
employment/unemployment are those of Lechner and Wunsch (2009), Fitzenberger et al.
(2010), Lechner et al. (2011), and McGuinness et al. (2014), depending on the section of
the population being targeted, but overall they reported a positive linkage.
Concerning the research on training in the 2000s (Larsson, 2002 - on earnings as
well; Stenberg, 2003 - on mobility between branches and on earnings; Weber and Hofer,
2003; Graversen, 2004; Hujer et al., 2004; Rosholm and Svarer, 2004; Centeno et al., 2005
- on earnings as well; Hogelund and Holm, 2005; Aakvik and Dahl, 2006; Meadows and
Metcalf, 2008; Rosholm and Skipper, 2009), no positive impact of training on employment
probability in European labour markets was found. According to Rosholm and Skipper
(2009) training raised the unemployment rate of participants but this effect disappeared over
time and this would indicate a locking-in effect, i.e. technical knowledge which is specific
to a particular production process and is not transferable to other processes. Other research
(Malmberg-Heimonen and Vuori, 2005; Steiger, 2005; Andren and Andren, 2006 -
unobservables slightly increased the effect for those treated; Lechner et al., 2007 - on
earnings as well; Cueto and Mato, 2009 - the locking-in effect found regarding trainees
suggested decreasing labour mobility; Lechner et al., 2011 - on earnings as well) found that
the employment effects of training were mixed, i.e. there were positive and negative results.
The findings suggest that training programmes seem to have had some positive
effects on employment and no effects on earnings. Moreover, the effects on the former
appear to diminish over time. The negative effects reported by several evaluations can be
explained, on the one hand, by a locking-in effect, and on the other by the fact that some
participants seemed to enrol in training merely in order to collect unemployment insurance
benefits (Cueto and Mato, 2009).
Micro-econometric analyses usually confirm that training had “mixed” results, but
nearly always a statistically insignificant impact on the participants’ prospects of
employment. Training might help an unemployed person to return to work faster and
because another unemployed worker therefore finds a job more slowly the training
programme is lacking effectiveness (Boone and van Ours, 2004). On the other hand, macro-
economic studies have reached the conclusion that training was the only category of active
employment policy that appears to have had a notable positive effect on the overall
performance of the labour market (CEC, 2006:145).
2.3 Mismatch and over-education
According to Chevalier and Lindley (2007), over-education can be defined as not being in a
graduate job when a person has a degree, thus resulting in skill mismatching. In general, the
vast majority of studies during the period 1990-2000 have indicated greater prevalence of
over-education rather than under-education (Green et al., 1999).
Despite a great deal of American and European empirical evidence being available
on the subject of over-education, it has been argued that “a solid relation [regarding the
over-education / under-education literature] with a formal theory of the labour market is
lacking” (Hartog, 1997).
According to human capital theory, over-education is not a permanent occurrence
and is the result of a poor match between employer and employee. This appears to go
against the empirical evidence, which suggests there is always a large percentage of the
9 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
labour force that is over-educated. It is possible that there is always over-education in the
labour market generally, but for each individual it is short lived. However, it could also be
the case that an individual chooses to be over-educated for a position, temporarily, so as to
remain in touch with the labour market in order to find a better job in the future. From this
point of view, over-education could be thought of as being a sort of human capital
investment (Green et al., 1999).
A different interpretation of over-education is offered by matching theory. Under
this lens, there might be a poor match between employer and employee causing over-
education, often resulting in the worker looking for a better match elsewhere. The fact that
both over- and under-education are to be found lends credence to the opinion that they are
both indications of the occurrence of poor matching in the labour market. In this instance,
over-education would be just short lived for the worker concerned (Green et al., 1999).
However, when persistent over-education occurs, according to Patrinos (1997), the focus
needs to be shifted away from the individual and his/her characteristics towards institutions
and policies regarding employment and vocational training across the focal society and its
political economy. The next section presents the micro-econometric work of the research.
3. Micro-Level of Analysis II: Econometric Analysis for Greece
3.1 The econometric analysis: The logit model for applying the micro-data of the
Greek LFS
In this research, the individual anonymised records (micro-data) of the 1992, 1994 and 2000
Labour Force Survey (LFS) for both employed and unemployed (1.5% of the total population
of each area) are examined, covering the spring and early summer, namely from the 14th to
26th week of the year. The reason these years are chosen is because 1992 was the first year in
the Greek LFS questionnaire with detailed questions on training, 1994 was the first year after
the end of the Community Support Framework (CSF)-1, whereas 2000 was one year after the
end of the CSF-2.
A logistic regression model is used for studying differences between those that did
participate in training programmes and those that did not. Moreover, regression models allow
for group comparisons by adjusting for demographic and socioeconomic variables. All three
years have merged together in order to take advantage of the time-series features of the data
(three time-sets of observations in 1992, 1994 and 2000) and used dummies for the years
instead. One logit model for all three areas under examination (Central Macedonia, Attica
and the rest of Greece) with all the main effects, all variables of interest, plus all the control
variables has been generated and has been run in a pooled format. Namely, all the available
data have pooled together into one database. Also, some of the categorical variables with few
observations (types of training) have been aggregated in order to increase the observations
within each cell, so as to avoid exceptionally large coefficients and confidence intervals.
The base (or reference) categories are those with which the rest of the corresponding
variables are compared. The reference categories are chosen so as to match the needs of the
research.2 In the next sub-section, the first part of the micro-level econometric analysis of the
paper is discussed.
3.2 Main effects
The Table 1 presents the results (main effects), namely, the estimated coefficients (B), the
standard errors (S.E.) and the p values for each explanatory variable in the logistic regression
2 Τhe working age population is between 14-65 years old. However, SPSS would not accept these age limits,
defaulting to 13 and 66 years old, so people from 15 to 64 years of age were included, which the programme was
able to compute.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 10
for unemployment in Greece. Column “Sig.” (level of statistical significance or p value)
provides the coefficients for the variables and those above 0.05 are not statistically
significant. In Table 1, bk is the log of the odds, whereas Exp (bk) is the odds ratio.
The descriptive statistics of the logit model are summarised in Table 2 (see in
appendix). After taking into account missing records, restricting the sample by age (15-64
years old) and removing the non-active population, Table 3 (see in appendix) shows the
numbers of records eligible for analysis in the LFS samples.
Table 1: Results (main effects) for Greece, 1992, 1994 and 2000 (parameter
estimates kb, standard errors (s.e.), p-values, exponent of kb
)
Variables bk S.E. Sig. Exp (bk)
Gender 0 .915 0 .019 0.000 2.497
Marital status -0.398 0.039 0.000 0.671
Aged 15-24 ref. ref. ref. ref.
Aged 25-34 -1.023 0.024 0.000 0.359
Aged 35-44 -1.706 0.029 0.000 0.182
Aged 45-64 -1.977 0.031 0.000 0.139
University graduates ref. ref. ref. ref.
MSc or PhD holders 0.110 0.183 0.546 1.116
TEI graduates 0.371 0.046 0.000 1.449
12 years of schooling 0.601 0.038 0.000 1.824
9 years compulsory education 0.550 0.044 0.000 1.734
Primary school graduates and below 0.518 0.040 0.000 1.679
Rest of Greece ref. ref. ref. ref.
Attica 0.083 0.041 0.046 1.086
Central Macedonia -0.075 0.041 0.064 0.927
Rural areas ref. ref. ref. ref.
Athens area 0.738 0.050 0.000 2.091
Thessaloniki area 0.787 0.054 0.000 2.196
Rest of urban areas 0.899 0.030 0.000 2.457
Semi-urban areas 0.518 0.037 0.000 1.679
Non-participation in training course(s) ref. ref. ref. ref.
Training -0.013 0.052 0.808 0.987
Citizenship 0.077 0.058 0.179 1.080
Year 1992 ref. ref. ref. ref.
Year 1994 0.025 0.022 0.266 1.025
Year 2000 0.055 0.033 0.096 1.056
Constant -2.262 0.062 0.000 0.104
Females, non-married individuals, people in the age group 15-24 years old, people
who lived either in the Athens or Thessaloniki areas, the other urban areas or semi-urban
areas were more likely to be unemployed than males, married people, people aged between 25
to 64 and those in rural areas. University graduates had more chances of finding a job
compared to all other educational categories apart from MSc or PhD holders (these
differences were not found significant). These results are in contrast to some studies which
have asserted the opposite. The variable ‘immigrant status’ was found to be statistically non-
significant. Most importantly, the participation in vocational training programmes did not
seem to reduce the odds of unemployment, that is, training was found to be statistically non-
significant during the first and the second CSFs. This means that the results of training
11 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
variables are not compatible with the human capital theory. In other words, the more trained a
person was did not affect his chances of finding a job, in Greece, during the time period of
CSFs 1 and 2. The same results on training were found for other Greek regions and the entire
country as well (see Livanos, 2007 and 2009; Rodokanakis, 2010a and 2010b; Rodokanakis
and Vlachos, 2013 and 2019). The exceptions are the findings for the region of Eastern
Macedonia and Thrace in 2000 concerning the training variables ‘apprenticeship’ and
‘continuing vocational training (CVT)’ (less likely to be unemployed than the non-trainees -
see Rodokanakis and Vlachos, 2012).
Whether or not someone lived in Central Macedonia in 1992, 1994 or 2000 was
statistically non-significant. By contrast, people who lived in the region of Attica were more
likely to be unemployed than those living in the rest of Greece. Both of the years 1994 and
2000 were found to be statistically non-significant, i.e. the variable ‘time’ did not influence
the probability of being unemployed.
In the main, the econometric results of this paper for Greece confirm the human
capital theory concerning education, namely, university graduates had higher probabilities of
finding a job than people from lower educational categories. However, this was not the case
in the field of training, since this variable was found to be statistically non-significant. Thus, it
would appear that matching theory has better explanatory power than human capital theory in
the Greek context. This is because the former perspective holds that those with more
education need less training and in Greece there are many over-educated people.
3.3 Interaction effects among variables
For the 1992, 1994 and 2000 samples together, I fitted the interaction effects between
education and gender, age groups and education, age groups and areas, age groups and years,
gender and years, as well as education and residence location, years and education, and years
and areas. Also, I fitted the interaction effects between training and age groups, training and
level of education, training and geographical areas or residence location, and training and
years.
In all tables of the interaction effects analysis, as with the main effects, the variable
“MSc or PhD holders” was statistically non-significant. According to Table 4-1, females
when compared to males, who were both Technological Educational Institutions (TEI)
graduates, had lower probabilities of being employed in comparison to the case where both
males and females were University graduates. In addition, females who were TEI graduates
were 1.46 times less likely to be employed than males and this was similar for the remaining
three educational categories in terms of gender.
Also, concerning age group and educational category, someone who was between 15
and 24 years old in the four educational categories was less likely to be unemployed in
relation to those in this age group who were university graduates. The same applied to those
aged 25-34. Moreover, people in the age group 45-64 were less likely to be employed than
those in the same age group who were university graduates. In addition, in Attica, people aged
35-64 were more likely to be unemployed than those between 15 and 24 in the same region.
Furthermore, someone aged 15-44 in all residential locations (Athens area, Thessaloniki area,
semi-urban areas and rest of the urban areas) had less probability of being unemployed when
compared to those in the same age group in rural areas; however, the opposite was the case in
the age group 45-64. Moreover, females, when compared to males, had a lower probability of
being unemployed in 1994 than in 1992. Age groups 15-24 and 25-34 in 2000 were less likely
to be unemployed than the same age groups in 1992. In contrast, people in the age groups 35-
44 and 45-64 were less likely to be employed than those in the same age groups in 1992.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 12
Table 4.1: Interactions with education and gender, age groups and education, age
groups and areas, age groups and years, gender and years (variables in the equation)
Variables bk S.E. Sig. Exp (bk)
Gender and University graduates ref. ref. ref. ref.
Gender and MSc or PhD holders -0.286 0.385 0.457 0.751
Gender and TEI graduates 0.381 0.095 0.000 1.464
Gender and twelve years of schooling 0.559 0.078 0.000 1.748
Gender and nine years compulsory education 0.902 0.089 0.000 2.465
Gender and primary school graduates and below 0.681 0.079 0.000 1.976
Aged 15-24 and University graduates ref. ref. ref. ref.
Aged 15-24 and MSc or PhD holders -0.976 1.241 0.431 0.377
Aged 15-24 and TEI graduates -1.130 0.187 0.000 0.323
Aged 15-24 and twelve years of schooling -0.905 0.156 0.000 0.404
Aged 15-24 and nine years compulsory education -1.487 0.174 0.000 0.226
Aged 15-24 and primary school graduates and below -1.929 0.155 0.000 0.145
Aged 25-34 and University graduates ref. ref. ref. ref.
Aged 25-34 and MSc or PhD holders 0.510 0.638 0.424 1.666
Aged 25-34 and TEI graduates -0.784 0.163 0.000 0.457
Aged 25-34 and twelve years of schooling -0.748 0.131 0.000 0.473
Aged 25-34 and nine years compulsory education -0.931 0.154 0.000 0.394
Aged 25-34 and primary school graduates and below -1.063 0.128 0.000 0.345
Aged 35-44 and University graduates ref. ref. ref. ref.
Aged 35-44 and MSc or PhD holders 0.651 0.717 0.364 1.918
Aged 35-44 and TEI graduates -0.357 0.193 0.065 0.700
Aged 35-44 and twelve years of schooling -0.071 0.153 0.645 0.932
Aged 35-44 and nine years compulsory education 0.047 0.177 0.791 1.048
Aged 35-44 and primary school graduates and below 0.052 0.146 0.723 1.053
Aged 45-64 and University graduates ref. ref. ref. ref.
Aged 45-64 and MSc or PhD holders -0.329 0.624 0.599 0.720
Aged 45-64 and TEI graduates 0.652 0.157 0.000 1.919
Aged 45-64 and twelve years of schooling 0.431 0.126 0.001 1.539
Aged 45-64 and nine years compulsory education 0.717 0.146 0.000 2.049
Aged 45-64 and primary school graduates and below 0.850 0.120 0.000 2.339
Aged 15-24 and Attica ref. ref. ref. ref.
Aged 25-34 and Attica -0.082 0.104 0.433 0.922
Aged 35-44 and Attica 0.265 0.119 0.026 1.303
Aged 45-64 and Attica 0.481 0.121 0.000 1.618
Aged 15-24 and Central Macedonia ref. ref. ref. ref.
Aged 25-34 and Central Macedonia 0.031 0.101 0.759 1.031
Aged 35-44 and Central Macedonia 0.067 0.120 0.578 1.069
Aged 45-64 and Central Macedonia -0.012 0.126 0.927 0.989
Aged 15-24 and rural areas ref. ref. ref. ref.
Aged 15-24 and Athens area -1.329 0.149 0.000 0.265
Aged 15-24 and Thessaloniki area -1.650 0.166 0.000 0.192
Aged 15-24 and rest of urban areas -1.245 0.096 0.000 0.288
Aged 15-24 and semi-urban areas -0.903 0.115 0.000 0.405
13 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Aged 25-34 and rural areas ref. ref. ref. ref.
Aged 25-34 and Athens area -0.988 0.153 0.000 0.373
Aged 25-34 and Thessaloniki area -1.331 0.166 0.000 0.264
Aged 25-34 and rest of urban areas -1.054 0.099 0.000 0.348
Aged 25-34 and semi-urban areas -0.715 0.118 0.000 0.489
Aged 35-44 and rural areas ref. ref. ref. ref.
Aged 35-44 and Athens area -0.667 0.172 0.000 0.513
Aged 35-44 and Thessaloniki area -0.930 0.190 0.000 0.395
Aged 35-44 and rest of urban areas -0.594 0.113 0.000 0.552
Aged 35-44 and semi-urban areas -0.454 0.134 0.001 0.635
Aged 45-64 and rural areas ref. ref. ref. ref.
Aged 45-64 and Athens area 1.506 0.086 0.000 4.509
Aged 45-64 and Thessaloniki area 1.324 0.112 0.000 3.758
Aged45-64 and the rest of urban areas 1.097 0.088 0.000 2.994
Aged 45-64 and semi-urban areas 0.813 0.103 0.000 2.255
Gender and year 1992 ref. ref. ref. ref.
Gender and year 1994 -0.099 0.045 0.028 0.906
Gender and year 2000 0.060 0.052 0.243 1.062
Aged 15-24 and year 1992 ref. ref. ref. ref.
Aged 15-24 and year 1994 -0.060 0.054 0.268 0.942
Aged 15-24 and year 2000 -0.961 0.074 0.000 0.382
Aged 25-34 and year 1992 ref. ref. ref. ref.
Aged 25-34 and year 1994 -0.013 0.055 0.815 0.987
Aged 25-34 and year 2000 -0.331 0.065 0.000 0.718
Aged 35-44 and year 1992 ref. ref. ref. ref.
Aged 35-44 and year 1994 -0.118 0.059 0.046 0.889
Aged 35-44 and year 2000 0.351 0.070 0.000 1.420
Aged 45-64 and year 1992 ref. ref. ref. ref.
Aged 45-64 and year 1994 0.085 0.060 0.157 1.089
Aged 45-64 and year 2000 0.449 0.076 0.000 1.567
Constant -0.502 0.130 0.000 0.605
According to Table 4-2, people aged 25-64 who had participated in vocational training
courses were more likely to be unemployed than those 15-24 years old who had also done so.
In addition, those who undertook training and were residents of the Thessaloniki area or the
rest of the urban areas had more chances of finding a job in relation to people in agrarian
areas who also participated in such courses.
Table 4.2: Interactions with training (variables in the equation)
Variables bk S.E. Sig. Exp (bk)
Gender and training 0.025 0.101 0.806 1.025
Aged 15-24 and training ref. ref. ref. ref.
Aged 25-34 and training 0.408 0.112 0.000 1.503
Aged 35-44 and training 0.484 0.149 0.001 1.623
Aged 45-64 and training 0.757 0.175 0.000 2.132
University graduates and training ref. ref. ref. ref.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 14
MSc or PhD holders and training -18.519 8563,539 0.998 0.000
TEI graduates and training 0.179 0.324 0.580 1.196
Training and twelve years of schooling 0.146 0.325 0.652 1.158
Training and nine years compulsory
education 0.005 0.353 0.989 1.005
Training and primary school graduates
and below -0.249 0.411 0.545 0.780
Training and the rest of Greece ref. ref. ref. ref.
Training and Attica -0.261 0.197 0.186 0.771
Training and Central Macedonia 0.452 0.250 0.070 1.572
Training and rural areas ref. ref. ref. ref.
Training and Athens area -0.422 0.250 0.091 0.656
Training and Thessaloniki area -0.992 0.305 0.001 0.371
Training and the rest of urban areas -0.408 0.179 0.022 0.665
Training and semi-urban areas -0.014 0.216 0.947 0.986
Training and year 1992 ref. ref. ref. ref.
Training and year 1994 0.360 0.212 0.089 1.433
Training and year 2000 0.021 0.183 0.908 1.021
Constant -2.243 0.062 0.000 0.106
According to Table 4-3, those who had been educated up to lyceum graduate level (12
years of schooling) living in the rest of the urban areas and not in rural ones, had a higher
probability of being unemployed than university graduates residing in the same areas. This
was also the case for those in semi-urban areas and in the Athens area, but in the Thessaloniki
area this was so only for people with up to a high-school graduate level of education (nine
years compulsory education). University graduates in Attica were less likely to be
unemployed than in the rest of Greece. In both Attica and Central Macedonia, TEI, lyceum
and high-school graduates were more likely to be employed than their corresponding
educational categories in the rest of the country. Only those completing primary school
education or below this level in both the NUTS-2 regions under investigation were more
likely to be unemployed than the same educational category in the rest of Greece.
Table 4.3: Interactions with education and areas* (variables in the equation)
Variables bk S.E. Sig. Exp (bk)
University graduates in Athens area ref. ref. ref. ref.
MSc or PhD holders in Athens area 18.970 14594,110 0.999 17330000
TEI graduates in Athens area 0.116 0.171 0.496 1.123
Twelve years of schooling in Athens area 0.492 0.140 0.000 1.635
Nine years compulsory education in
Athens area 1.187 0.153 0.000 3.277
Primary school graduates and below in
Athens area 2.049 0.142 0.000 7.762
University graduates in Thessaloniki area ref. ref. ref. ref.
MSc or PhD holders in Thessaloniki area 18.777 14594,110 0.999 14280000
TEI graduates in Thessaloniki area -0.204 0.202 0.314 0.816
Twelve years of schooling in Thessaloniki
area 0.157 0.163 0.335 1.170
15 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Nine years compulsory education in
Thessaloniki area 0.578 0.189 0.002 1.783
Primary school graduates and below in
Thessaloniki area 1.617 0.167 0.000 5.039
University graduates in the rest of urban
areas ref. ref. ref. ref.
MSc or PhD holders in the rest of urban
areas 19.015 14594,110 0.999 18110000
TEI graduates in the rest of urban areas 0.206 0.176 0.244 1.228
Twelve years of schooling in the rest of
urban areas 0.607 0.144 0.000 1.834
Nine years compulsory education in the
rest of urban areas 0.986 0.157 0.000 2.680
Primary school graduates and below in the
rest of urban areas 1.905 0.144 0.000 6.721
University graduates in semi-urban areas ref. ref. ref. ref.
MSc or PhD holders in semi-urban areas 0.442 16746,825 1.000 1.555
TEI graduates in semi-urban areas 0.458 0221 0.038 1.581
Twelve years of schooling in semi-urban
areas 0.635 0.182 0.000 1.886
Nine years compulsory education in semi-
urban areas 0.814 0.198 0.000 2.258
Primary school graduates and below in
semi-urban areas 1.493 0.181 0.000 4.450
University graduates in the rest of Greece ref. ref. ref. ref.
University graduates in Attica -0.640 0.085 0.000 0.527
University graduates in Central Macedonia 0.003 0.109 0.981 1.003
MSc or PhD holders in the rest of Greece ref. ref. ref. ref.
MSc or PhD holders in Attica -0.283 0.634 0.656 0.754
MSc or PhD holders in Central Macedonia 0.176 0.762 0.817 1.192
TEI graduates in the rest of Greece ref. ref. ref. ref.
TEI graduates in Attica -0.855 0.077 0.000 0.425
TEI graduates in Central Macedonia -0.389 0.105 0.000 0.678
Twelve years of schooling in the rest of
Greece ref. ref. ref. ref.
Twelve years of schooling in Attica -0.807 0.050 0.000 0.446
Twelve years of schooling in Central
Macedonia
-0.384 0.069 0.000 0.681
Nine years compulsory education in the
rest of Greece ref. ref. ref. ref.
Nine years compulsory education in Attica -0.395 0.069 0.000 0.674
Nine years compulsory education in
Central Macedonia
-0.246 0.095 0.010 0.782
Primary school graduates and below in the
rest of Greece ref. ref. ref. ref.
Primary school graduates and below in
Attica
0.395 0.069 0.000 1.485
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 16
Primary school graduates and below in
Central Macedonia
0.246 0.095 0.010 1.279
Constant -0.502 0.130 0.000 0.605
*Rural areas are set as reference across all interactions with areas
According to Table 4-4, all educational categories (apart from MSc or PhD holders) in
1994 were more likely to be unemployed than university graduates and the same was true for
2000. Also, in 1994, those living in Athens or Thessaloniki were more likely to be
unemployed than people in rural areas, whilst the opposite was the case for those living in
semi-urban areas in 1994 and 2000, as well as in the rest of the urban areas in 2000. Finally,
in 1994 it was more likely that someone was unemployed in Attica than in the rest of Greece.
Table 4.4: Interactions with years and education, and with years and areas* (variables
in the equation)
Variables bk S.E. Sig. Exp (bk)
Year 1994 and University graduates ref. ref. ref. ref.
Year 1994 and MSc or PhD holders -0.313 0.46 0.496 0.731
Year 1994 and TEI graduates 0.407 0.123 0.001 1.502
Year 1994 and twelve years of schooling 0.447 0.102 0 1.563
Year 1994 and nine years compulsory education 0.446 0.115 0 1.563
Year 1994 and primary school graduates and below 0.485 0.105 0 1.624
Year 2000 and University graduates ref. ref. ref. ref.
Year 2000 and MSc or PhD holders -0.649 0.436 0.136 0.522
Year 2000 and TEI graduates -0.059 0.129 0.65 0.943
Year 2000 and twelve years of schooling 0.16 0.108 0.14 1.173
Year 2000 and nine years compulsory education 0.163 0.124 0.188 1.177
Year 2000 and primary school graduates and below 0.53 0.113 0 1.698
Year 1994 and rural areas ref. ref. ref. ref.
Year 1994 and Athens area 0.17 0.071 0.016 1.186
Year 1994 and Thessaloniki area 0.188 0.096 0.051 1.207
Year 1994 and rest of urban areas 0.044 0.072 0.543 1.045
Year 1994 and semi-urban areas -0.294 0.087 0.001 0.745
Year 2000 and rural areas ref. ref. ref. ref.
Year 2000 and Athens area -0.084 0.08 0.295 0.919
Year 2000 and Thessaloniki area -0.1 0.105 0.338 0.904
Year 2000 and rest of urban areas -0.173 0.08 0.03 0.841
Year 2000 and semi-urban areas -0.275 0.095 0.004 0.759
Year 1994 and the rest of Greece ref. ref. ref. ref.
Year 1994 and Attica 0.213 0.052 0.000 1.238
Year 1994 and Central Macedonia 0.126 0.069 0.067 1.134
Year 2000 and the rest of Greece ref. ref. ref. ref.
Year 2000 and Attica -0.029 0.055 0.601 0.971
Year 2000 and Central Macedonia 0.140 0.073 0.057 1.150
Constant -1.914 0.103 0 0.147
* Year 1992 is set as reference across all interactions with years
4. Conclusion
The econometric results for Greece (main effects) support the human capital theory with
17 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
regards to education, i.e. university graduates had a higher probability of finding
employment than people with lower education levels. Hence, the findings of this paper
support the main policy lessons of human capital theory in the field of education. However,
this was not so in the case of training, as this variable emerged as being statistically non-
significant.
Regarding the interaction effects analysis, the findings in relation to education
support the human capital theory, with the exceptions to this being the relation between
educational level and age groups 15-34. Hence, most of the educational variable findings
concerning this aspect of the analysis did not support human capital theory. In particular, the
more educated a person was did not mean an improvement in his/her position in the Greek
labour market during the period 1988-2000. These findings on education are consistent with
those of some studies and aggregate statistics mentioned in section 1, which assert that
university graduates in Greece were not in a better position in the labour market than non-
university degree holders with regards to the probability of finding a job.
The results of the interaction effects analysis for training are not different from the
findings of the main effects, with the exceptions being the age groups 25 to 64, who were
more likely to be unemployed in relation to those 15-24 years old and concerning training,
people who lived in Thessaloniki or in the rest of the urban areas were more likely to be
employed than those living in rural ones. In other words, the chances of finding a job did not
change when training is counted as an additional qualification in relation to the other
characteristics of individuals in the LFS. These results were expected, first, because the
findings on all training variables in the logit model were non-significant and second, because
the number of training records used was apparently even smaller when the interaction effects
were examined, hence logically, the same outcomes would be expected.
The results support matching theory better than human capital theory, because the
former supports the perspective that more education leads to less training and Greece has
many over-educated people. This supports even more the stance that the human capital
theory could (and still can) not provide an explanation for the training configuration found in
Greece. One of the contributions of this paper is that, given the experience in Greece, it
appears that abstract micro-level theories of skills mismatch, like the human capital theory,
cannot be applied in political economies where labour markets cannot absorb high skills and
where demand for jobs requiring these is weak.
The mismatch between supply and demand for labour could be partially attributed to
the training mismatch, but this was only one cause of the unemployment problem. The
econometric findings on training are in line with those of Livanos (2007 and 2009) and to the
best of my knowledge, our studies are the only econometric studies for Greece on this topic
based on LFS micro-data.
The problems of today had already been identified in the late 1980s, but apparently
little has been done to rectify them. Of course the current crisis has not been magnified in
Greece because of the ineffectiveness and inefficiency of these training programmes, but has
to do with the structural problems already existing in the economy and the labour market
well before the crisis. The country entered the euro under these conditions and dynamics and
their non-resolution contributed, to an extent, to the country’s current economic and social
bottlenecks.
It is concluded that the cascading of EU money for training and the EU training
policies, were not effective in the case of Greece. Training could be ineffective even in
Northern European countries, but the reasons underlying this were not be the same as those
in Greece. One key particularity of that nation’s circumstance is the very high levels of
unemployment amongst the skilled labour force.
In other words, the human capital theory on training does not appear to be applicable
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 18
in the Greek context. Still, for the period under investigation, the high-skilled labour force
could not be absorbed in Greece. It appears that a strategic plan to create demand for training
was absent.
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APPENDIX
TABLE 2: DESCRIPTIVE STATISTICS OF THE LOGIT MODEL
The reference or base categories are in bold
Variables/Area/Year Frequencies Percent
Employed 138,405 90,4%
Unemployed 14,628 9,6%
Males 94,943 62,0%
Females 58,090 38,0%
Non-married 10,339 6,8%
Married or divorced or widows 142,694 93,2%
Aged 15-24 19,395 12,7%
Aged 25-34 39,975 26,1%
Aged 35-44 39,708 25,9%
Aged 45-64 53,955 35,3%
Training 4,208 2,7%
Non-participation in training
Greek Citizenship
148,825
149,881
97,3%
97,9%
Foreigner Ctizenship 3,152 2,1%
Athens area 45,994 30,1%
Thessaloniki area 12,662 8,3%
Rest of urban areas 36,433 23,8%
Semi-urban areas 18,989 12,4%
Rural areas 38,955 25,5%
MSc or PhD holders 554 0,4%
University graduates 15,048 9,8%
TEI graduates 11,358 7,4%
Twelve years of schooling 40,762 27,8%
Nine years compulsory education 14,532 9,9%
Primary school graduates and below 64,561 44,0%
Central Macedonia 24,398 15,9%
Attica 53,773 35,1%
Rest of Greece 74,862 48,9%
Year 1992 53,297 34,8%
Year 1994 65,858 43,0%
Year 2000 33,878 22,1%
Table 3: Numbers of records eligible for analysis in the LFS samples
Year Geographical level No. of records
1992 Greece 53,297
Central Macedonia 9,290
Attica 20,301
Rest of Greece 23,706
1994 Greece 65,858
Central Macedonia 9,543
Attica 22,399
Rest of Greece 33,916
2000 Greece 33,878
Central Macedonia 5,565
Attica 11,073
Rest of Greece 17,240
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 22
Community Involvement in event planning: Cases from Greek Festival
Market
Abstract:
It has been stated from various researchers that local communities play significant role to the
development and success of festivals and events. The latter may have a positive or negative
contribution to local society, economy, tourism and culture and their success is based mainly
on event planning orientation. Current paper approaches community involvement and
examines its levels to Greek festivals. A quantitative research took place to festival managers
and factor analysis was implemented in order to develop factors that include categories of
community involvement variables. Additionally, cluster analysis revealed that there are
different groups of festivals based on their mentality against community involvement. Those
groups presented certain characteristics and further statistical analysis showed that there is
strong correlation between several attributes and cluster categorization.
Keywords: community involvement, festivals, factor analysis, cluster analysis
Sofoklis Skoultsos1 and Alexios- Patapios Kontis2
1 Corresponding-Address: Dr. Sofoklis Skoultsos, Adjunct Lecturer, University of The Aegean. Email:
[email protected]. Sokratous 13, N. Irakleio Attikis, 14122. 2 Corresponding-Address: Dr. Alexios- Patapios Kontis, Adjunct Lecturer, University of The Aegean. Email:
23 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Introduction
During last decades event industry has been developed rapidly at a global level. Various
destinations and local authorities approach all kind of events and festivals as means for further
development of local societies. Taking into account the strong relation between tourism and
events, the latter have been exploited in order to increase tourism flows at the host destination.
These tourism flows can be used as means of economic development (Ridolfi et al. 2017).
Additionally, events now represent a significant part of the tourism industry, especially when
they are related directly to culture. Additionally, destinations exploit culture as an alternative
offered experience and product to differentiate from the traditional mass tourism (Sarantakou,
Tsartas, & Bonarou, 2018; Sarantakou & Kontis, 2016) This fact, highlights the global trend
to special interest tourism products that have been argued from various researchers (Tsartas &
Sarantakou, 2016). As a result, various researchers have been focused on events as a separate
field of study and form of tourism. Impacts, motivation, event design, event experience,
events as tourism products etc. are some of the main issues discussed in the event literature.
Besides the above, another issue that is of great importance is event planning. Planning is
essential in order to achieve success in festival management and inevitably contains a wide
range of different aspects. Current paper focuses on level of community involvement as an
aspect of event planning. Managers for Greek festivals were selected as sample in order to
examine the level of local people engagement to festival management and implementation.
2. Literature Review
It is widely accepted that an event exploits, creates and rejuvenates the host area and can
affect a lot the local community (Picard & Robinson, 2006, p. 11). Although each event lasts
for a short period of time, their impacts (positive or negative) are obvious either for Mega,
Hallmark or Local events. Undoubtfully, there is a correlation between the level of these
impacts and the size of the event (Allen J., O’Toole W., McDonnell I. & Harris R., 2002).
Events can affect local economy, culture, society and tourism. The most difficult impacts to
be measured are the ones on the society and culture, although they are very important for the
host areas (Mason & Cheyne, 2000). Several researches tried to adapt measuring tools for
social impacts from the local people perspective (Delamere, 2001; Delamere et.al., 2001).
Events - especially the ones included in the category of Hallmark Events - can be
closely related to life and identity of local people. It has to be mentioned that various
researches examined the identity as key element of festival (Azara & Crouch, 2006; McCabe,
2006;). Arcodia & Whitford (2006) examined the concept of social capital and how it can be
developed through practices like building community resources and social cohesion. They
came up with the conclusion that positive social impacts should be the initial goal for event
managers.
Needless to say, in certain situations events may cause negative impacts to the local
society. Specifically, the large amount of people that visits a limited area for a short period of
time can contribute to rapid changes at the local environment and everyday life of local
people such as: price inflation, increase of crime, traffic conjunction etc. (Dwyer et.al, 2000;
Arcodia & Whitford, 2007; Bowdin et.al., 2011). All the mentioned impacts have a strong
negative result on the approach of local people to the festival, especially in cases were local
people are neglected from the organization of the festival. Various researchers argued that the
negative impacts of an event or festival can be relieved when local people are involved
(directly or indirectly) with the management and the whole organization of the festival or
event (Skoultsos, 2009). Moreover, long-term success of an event depends a lot on the
acceptance of the festival from locals. As a result, it can be stated that community
involvement is essential and should be considered as a major factor upon which a festival’s
success relies. As Getz (2007, p. 308) stated: “The ultimate in community acceptance is that
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 24
events become recognized as permanent ‘institutions’ in their community… ‘institutions’ can
only emerge through strong community support as measured by loyal attendance, committed
volunteers and political support…”.
The concept of community may be described with various definitions. Individuals can
self-identify themselves … “in terms of their home in terms of their home location or their
sense of belonging to a specific social group. Consequently, several distinct “communities”
may exist within a geographical area or neighborhood” (Rogers & Anastasiadou, 2011, p.
388). Another interesting definition is the one that highlights the importance of decision
making. Community is a “mutually supportive, geographically specific, social unit” (Mann,
2000, p. 18).
Apart from definition of community, various researchers have been focused on
community involvement and its importance for festivals, by examining the perspective of
local people (Fredline, 2000; Gursoy et.al., 2004). It is widely accepted that community
involvement leads to social coherence, increased sense of offering to the society, enhanced
local identity (especially at small and local festivals), community pride of local people etc.
(Hall, 1992; Mason & Beaumont-Kerridge, 2004; Fredline et.al., 2003; Arcodia & Witford,
2007; Skoultsos, 2009; Bowdin et.al., 2011). Additionally, an event may positively affect the
local community because it is an opportunity for leisure, personal development, recognition
(through volunteering) and social bonding (The Association of Festival Organizers, 2004).
The support and involvement of local community to a festival may be implemented in
various ways such as: volunteering, responsibilities of management, attendance, participation
decision making etc. All these forms of community involvement vary according to mindset
and managerial approach of festival managers. Moscardo (2007) argued that community
involvement should be one of the main elements of any festival and proposed a framework in
order to reach regional development through this particular mentality. Later on, Rogers &
Anastasiadou (2011) developed a framework to assess community involvement that consisted
of five indicators: involvement of schools; volunteering opportunities; participation in
decision making; accessibility; and business cooperation. The ultimate goal of the current
framework was to help authorities to improve their perspective on community involvement of
their festivals.
3. Research aims and objectives
Regarding the changing environment in the Greek Festival Market according to financial
crisis, event planning has been changing throughout the last decade. Moreover, taking into
account the importance of community involvement in the success of festival’s
implementation, current paper aims to explore the level of community involvement in Greek
festivals. Secondly, tries to highlight possible factors that may affect the approach that festival
managers have on the issue of community involvement. Based on the above analysis, the
following hypotheses were formulated in order to be tested through primary research:
H1. Variables of community involvement can be divided to different factors.
H2: There are different groups of festivals according to community involvement levels
at Greek festival market.
H3: Specific features of the festival affects levels of community involvement.
H3.1. There are specific characteristics of the surrounded area that affect the
approach of community involvement.
H3.2. There are specific characteristics of the perspective of festival managers
that affect the approach of community involvement
4. Methodology
The methodology that was finally implemented was quantitative research by questionnaire to
festival managers from the Greek festival market. The questionnaire contained a total number
25 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
of 20 questions. Seventeen of them were closed questions and three of them were open so as
the managers could express their opinion on several issues. The questionnaire was divided in
three sections: 1. Demographics of the festival (years of implementation, duration, host area
etc.), 2. Level of Community involvement (variables derived from event literature, opinions
etc.), 3. Contribution to local tourism product (efforts done for including the festival to the
local tourism product, success, opinions, perceptions on issues related to event tourism etc.).
Table 1: Variables (V) of community involvement to be tested
V1: There are local networks that contribute to the discovery of local artists (or
producers)
V2: There is a differentiated pricing policy for locals or/and for repeat visitors.
V3: There is a providence to include sponsorships from local enterprizes to the
festival.
V4: Promotional activities take place to the host area in order to increase the
sense of celebrating the festival’s identity and the inclusion of local citizens.
V5: Free (or affordable price) entrance.
V6: Local people are (or can be) volunteers at the festival.
V7: The majority of the festival’s employees are local citizens.
V8: Shows related to the festival’s program are performed for kids in public
places.
V9: Local citizens participate as volunteers at various positions in festival’s
management.
V10: Increase of participants’ social networking has been spotted because of the
festival.
V11: There is an assurance that the promotional activities of the festival aim to
attract local people.
V12: There are strong bonds between festival’s managers and local associations.
V13: Participation of local artists (or producers) in the festival program is a
strategy for the festival.
V14: Local people participate in decision making processes regarding festival’s
management issues.
V15: Taster shows are held around the festival’s area.
V16: There is an organizational committee that is responsible for communicating
with local associations.
V17: There is a providence for pricing facilitations (e.g. free transportation
coupons, discounts) to certain social groups of local citizens (e.g. students and
unemployed) during the festival.
As mentioned above, the scope of the primary research was to test H1, H2 and H3
hypotheses. According to this, factor and cluster analysis were implemented. Specifically,
factor analysis was used to decrease the number of variables (related to community
involvement) to a lower number of factors. Seventeen variables were selected and all of them
were based on event literature and previous research work of Rogers & Anastasiadou (2011)
(Table 1.). Selected variables were tested on a 5-point Likert Scale (5=Totally agree totally
1=Disagree). Furthermore, cluster analysis was used to examine if there are discernible
groups of festivals according to their specific characteristics. It was implemented in two steps:
Firstly, hierarchical cluster analysis was conducted to reveal the statistically reliable number
of clusters to be chosen. Further elaboration of data using k-means cluster was conducted for
three- and four- cluster solutions.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 26
4.1 Data Collection and Sample
In order to collect primary data to test the hypotheses, an online survey was conducted from
September 2017 to December 2017. The goal was to approach Greek festival managers
without focusing on a specific type or kind of festivals so as to avoid certain characteristics of
the respondents (or the festivals involved). The questionnaire was sent to a list of 150 festival
managers’ contacts. Each respondent had the opportunity to complete only one on-line
questionnaire (through online platform) and was informed that all the data were filled
anonymously. Finally, the total number of filled questionnaires was 126 and 104 were
appropriate for further analysis. Statistical software of SPSS was used for the statistical
analysis of the results. Initially, descriptive statistics were used to analyze sample’s
sociodemographic characteristics.
5. Results
5.1 Demographics
Table 2 and Table 3 present the basic “demographics” of the festivals participated in the
survey. The vast majority of the festivals have “Music” in their theme and activities and are
held during the summer period. Moreover, most of them have been implemented for 5 to 10
years and they last mainly from 2 to 5 days. All the other characteristics (Surrounded area,
average number of attendees per day) presented more scattered answers.
Table 2: “Demographics” of the participated festivals – part 1
Years of
implementation
Main theme of the
Festival3
Season of the year
up to 2 years 11.54% Music 75% Summer 59.62%
2 to 5 years 23.08% Film 25% Autumn 23.08%
5 to 10 years 40.38% Sports 14% Winter 1.92%
10 to15 years 11.54% Gastronomy 20% Spring 15.38%
15 to 20 years 7.69% Dance 41%
more than 20
years
5.77% Other 50%
Table 3: “Demographics” of the participated festivals – part 2
Surrounded Area Average number of
attendees per day
Duration
less than 2000
residents
17.31% less than 100 1.92% 1 day 3.85%
2.000 to 10.000
residents
17.31% 100-500 25.00% 2 days 38.46
%
10.000 to 50.000
residents
25.00% 500-1.000 36.54% 3 to 5 days 38.46
%
50.000 to 100.000
residents
23.08% 1.000-5.000 25.00% more than 5
days
19.23
%
more than 100.000
residents
17.31% 5.000-10.000 9.62%
less than 2000
residents
17.31% more than
10.000
1.92%
3 The respondent had the opportunity to fill more than one answer.
27 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Regarding the connection between the festival’s theme and activities with local
tradition, answers were diffused into two main categories: 44% answered that part of the
offered activities are directly linked to local tradition and 44% that there is no connection
between local tradition and the festival’s theme and activities. Only 12% answered that there
is a direct connection of the festival with the local tradition. Concerning the ratio of locals
and tourists, approximately 55% managers (54.35%) answered that due to their estimations
both categories are included at festival’s crowd. 34.78% declared that the festival attracts only
locals. Another critical question was the one for the festival manager’s perception upon the
importance of community involvement in the management of festivals. The answers were
divided with the following descending order: “Very Important” (50%), Absolutely essential
(26%), “Of Average Importance (22%), “Of little importance” (2%) and “Not important at all
(0%).
Table 4 presents the relative results in terms of festival’s relation with local tourism
product. Clearly, the majority (47,83%) of the participated managers clarified that they did
not make any effort to include the festival in the local area’s tourism product. Almost one
third of the sample declared that although they tried to make this connection their efforts were
unsuccessful. As a result, only 41% stated that their festival has been effectively (fairly and
adequately) utilized from the tourism industry. On the other hand, most of them believe that
the festival is successful. Only 4.4% stated that their festival is less successful. Taking
account, the answers about the impacts, it is obvious that festivals are not considered to have a
high positive impact on local tourism by managers. However, managers declared that they
have an extremely positive impact on society and on local culture.
Table 4: Festival’s relationship with local tourism product and level of success
Efforts have been made
to include festival in the
tourism product of the
local area.
The festival has been
effectively utilized by the
tourism industry.
How much successful
your festival can be
considered?
Yes,
successfully
21.74% Not at all 28.26% Not at all 0.0%
Yes,
unsuccessfully
30.43% Slightly 30.43% Less
successful
4.4%
No 47.83% Fairly 23.91% Adequately
successful
47.8%
Adequately 17.39% Very
successful
37.0%
Fully 0.00% Totally
successful
10.9%
Table 5: The festival has been positively affected:
Not at all Slightly Moderately Very Extremely
economy 8.7% 4.4% 32.6% 32.6% 21.7%
tourism 13.0% 15.2% 30.4% 19.6% 21.7%
culture 0.0% 4.4% 4.4% 28.3% 58.7%
society 2.2% 4.4% 10.9% 26.1% 52.2%
environment 6.8% 11.4% 36.4% 15.9% 27.3%
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 28
Table 6: Factors affecting the level of success for festivals:
Not
importan
t
Less
importan
t
Of
Average
importanc
e
Very
importan
t
Of Great
importanc
e
Stable Frequency 0.0% 2.2% 33.3% 44.4% 20.0%
Early Scheduling 0.0% 0.0% 2.2% 19.6% 78.3%
Appropriate placement of
employees (specialized in
event management) 0.0% 2.2% 10.9% 43.5% 43.5%
Level of event's production
quality (e.g. infrastructure) 0.0% 0.0% 19.6% 34.8% 45.7%
Holistic Experience 0.0% 0.0% 8.7% 43.5% 47.8%
Creation of bonds with local
society 0.0% 2.2% 15.2% 41.3% 41.3%
Effective promotion 0.0% 0.0% 2.2% 32.6% 65.2%
Regarding the factors that affect the level of success of a festival, the most important
one is “early scheduling” and secondarily “effective promotion”. The majority of answers
(82.6%) regarding “creation of bonds with local society” were equally split to “very
important” and “of great importance”.
5.2 Factor Analysis
First of all, regarding credibility of factor analysis, researchers state that in order to complete
factor analysis, number of respondents has to be five times greater than the number of the
selected items (Siomkos, 2005, p. 286). In the current study the number of participants was
104 and number of selected items 17 so the credibility is well stated. Table 7 shows the
variables that have been tested in the factor analysis. The majority of them gathered mean
over 3 with the highest at 3.92 and the lowest 1.87. Results from analysis (principal
components factor analysis with varimax rotation) revealed 5 factors with an eigenvalue of at
least 1.0 and explained 66.3% of Total variance. Scree plot (Figure 1) also shows that at least
5 is the appropriate number of derived factors. Table 8 presents the final results of factor
analysis: means for each variable item and its Standard Deviation4. The results clearly show
that there are variables that can be combined in five factors which can be described with the
following names: 1. Involvement of locals to management, 2. Strengthening the “bonds”, 3.
Networking, 4. Promotion to locals, 5. Communication of activities to the host area.
Table 7: Means and Standard Deviation of each community involvement variable
Community Involvement Variable Means Std. Deviation
V5: Free (or affordable price) entrance 3.92 1.18
V6: Local people are (or can be) volunteers at the festival. 3.92 1.094
V10: Increase of participants’ social networking has been spotted
because of the festival.
3.90 1.048
V11: There is an assurance that the promotional activities of the
festival aim to attract local people.
3.65 0.833
V13: Participation of local artists (or producers) in the festival
program is a strategy for the festival.
3.63 0.966
V12: There are strong bonds between festival’s managers and 3.60 1.102
4 Answers was based on 5-point Likert scale (1=not important, 5=extremely important).
29 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
local associations.
V4 Promotional activities take place to the host area in order to
increase the sense of celebrating the festival’s identity and the
inclusion of local citizens.
3.56
0.912
V9: Local citizens participate as volunteers at various positions in
festival’s management.
3.48 1.174
V7: The majority of the festival’s employees are local citizens. 3.33 1.194
V3: There is a providence to include sponsorships from local
enterprises to the festival. 3.31
1.107
V8: Shows related to the festival’s program are performed for
kids in public places.
3.27 1.217
V17: There is a providence for pricing facilitations (e.g. free
transportation coupons, discounts) to certain social groups of
local citizens (e.g. students and unemployed) during the festival.
3.13 1.293
V14: Local people participate in decision making processes
regarding festival’s management issues.
3.08 1.163
V16: There is an organizational committee that is responsible for
communicating with local associations. 3.04
1.114
V1: There are local networks that contribute to the discovery of
local artists (or producers)
2.44
1.05
V15: Taster shows are held around the festival’s area. 2.31 1.207
V2. There is a differentiated pricing policy for locals or/and for
repeat visitors. 1.87
1.098
Figure 1: Scree Plot
5.3 Cluster Analysis
Regarding cluster analysis’ results, dendrogram of Hierarchical analysis revealed that two-
clusters solution should be accepted. Nevertheless, k-means cluster analysis for three- and
four- cluster solutions was implemented in order to test other alternatives. Finally, the
solution of two clusters was chosen as the most effective differentiation of the sample. Table
9 presents the respective results of cluster analysis and the mean values of importance of each
created cluster to each of the tested variables. The first cluster represents more than the 2/3 of
the sample (69,2%) and presented a mean score of 3 to all variables included in the factor
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 30
analysis (2.93 including V17). Clearly, the 2nd cluster showed that all the tested variables of
community involvement took place in their management at high level.
Table 8: Community involvement variables divided in to 5 factors
Community development factors
and items
Factor
Loadin
g
Eigenvalu
e
Variance
explained
(%)
Cronbac
h Alpha
F1: Involvement of locals to
management
2.815 17.596 0.802
V6: Local people are (or can be)
volunteers at the festival.
.822
V9: Local citizens participate as
volunteers at various positions in
festival’s management.
.696
V14: Local people participate in
decision making processes
regarding festival’s management
issues.
.663
V7: The majority of the festival’s
employees are local citizens.
.612
V4: Promotional activities take
place to the host area in order to
increase the sense of celebrating the
festival’s identity and the inclusion
of local citizens.
.544
F2: Strengthening the “bonds” 2.110 13.189 0.612
V17: There is a providence for
pricing facilitations (e.g. free
transportation coupons, discounts)
to certain social groups of local
citizens (e.g. students and
unemployed) during the festival.
.706
V12: There are strong bonds
between festival’s managers and
local associations.
.684
V8: Shows related to the festival’s
program are performed for kids in
public places.
.630
V13: Participation of local artists
(or producers) in the festival
program is a strategy for the
festival.
.377
F3: Networking 2.005 12.533 0.617
V5: Free (or affordable price)
entrance.
.858
V1: There are local networks that
contribute to the discovery of local
artists (or producers)
.701
V10: Increase of participants’ social
networking has been spotted
because of the festival.
.464
F4: Promotion to locals 1.955 12.218 0.546
31 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
V3: There is a providence to
include sponsorships from local
enterprises to the festival.
.885
V11: There is an assurance that the
promotional activities of the festival
aim to attract local people.
.546
F5: Communication of activities
to the host area
1.774 11.088 0.668
V15: Taster shows are held around
the festival’s area.
.834
V16: There is an organizational
committee that is responsible for
communicating with local
associations.
.535
Total Variance Explained 66.624%
5.4 Characteristics of the revealed clusters
Furthermore, authors implemented additional statistical tests in order to check the correlation
between various answers of the questionnaire and cluster categorization. Specifically, chi-
square tests were implemented and the following variables (derived from the whole
questionnaire) appear to have a strong correlation with the final categorization of the clusters:
Characteristics of the surrounded area (x2=14.986, df=4, p=0,005). It seems that festivals
held at areas with low population tend to be categorized to the second cluster.
Theme of festival (Sports x2=8.206, df=1, p=0,004 and Dance x2=9.559, df=1, p=0,002):
It seems that sports and dance festivals tend to be included to the 2nd cluster.
Importance of festival’s acceptance from local citizens (x2=31.732, df=4, p=0,000): There
is a strong correlation between the opinion of the managers for the importance acceptance
among local people and cluster division. Managers of the 2nd cluster’s festivals appear to
believe that acceptance from local people is extremely important.
“Efforts have been made to include festival in the tourism product of the local area”
(x2=42.692, df=3, p=0,000) and “The festival has been effectively utilized by the tourism
industry” (x2=16.992, df=4, p=0,002): There is strong correlation between the answers in the
current question and cluster categorization. It seems that cluster 2 includes the majority of the
cases of festivals that made successful efforts to include the festival in the local area’s tourism
product. The same tendency appeared for the second question respectively.
The festival contributes positively to local economy (x2=18.092, df=5, p=0,003), tourism
(x2=19.649, df=5, p=0,001) and society (x2=24.899, df=6, p=0,000): Additionally, managers
of the festivals included in the 2nd cluster, tend to be more confident in terms of positive
contribution of the festival to economy, tourism and society.
Perspective on the definition of community (x2=16.162, df=4, p=0,003): Finally,
correlation found between managers’ perspective of community and cluster categorization. It
seems that the majority of the managers included in the second cluster, approach the concept
of community as “anything common that can support any group of people”.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 32
Table 9: “Community involvement” factor means for each cluster
Overall mean
(n=104)
Cluster 1 –
(n=72)
Cluster 2
(n=32)
F1: Involvement of locals to
management
3.47 3.06 4.40
F2: Strengthening the “bonds” 3.41 3.06 4.19
F3: Networking 3.42 3.15 4.04
F4: Promotion to locals 3.48 3.13 4.28
F5: Communication of activities to
the host area
2.67 2.40 3.28
Total to variables included in the
factor analysis5
3.35 3 4.13
Note: Answers was based on 5-point Likert Scale (5=Totally agree totally 1=Disagree)
6. Analysis and Discussion
At first, the above results reflect that the majority of Greek festivals are implementing
practices of community involvement in their management at least to a moderate extent. Table
7 shows clearly that none of the tested variables exceeded number 4 in the relative Likert
Scale and it can be stated that although managers comprehend the importance of community
involvement, this belief is not reflected by a relative and clarified mindset as well. It is
important to mention that only 30.8% showed a willingness to engage local people to their
management practices.
Additionally, the managers’ answers on the positive impact of festivals enlighten the
fact that festivals considered to be catalysts for local culture and social coherence, according
to their opinion. It can be arbitrarily derived that festival managers aim on positive
contribution to local culture and society and as a result they actually believe that their festival
contributes to these sectors. Social cohesion and festival’s approval from the locals are
considered to be important factors in the mentality of managers, which complies with
previous researches (Moscardo, 2007; Arcodia & Witford, 2006; Skoultsos 2014). Moreover,
the responses reveal several difficulties that Greek festivals should overcome. Specifically,
lack of “Early scheduling” has been referred as one of the main problems for Greek festivals
in previous findings (Skoultsos, 2014) which has been increased due to various obstacles
based on economic crisis and difficulties in sponsorships and grants from public sector.
Festival managers do not associate utilization of tourism industry and inclusion in the
tourism product with the success of a festival. The latter is an important outcome which
reflects the mindset of the majority of the participants. These results comply with previous
research which revealed that the vast majority of Greek festivals do not aim -actually - to the
tourism industry and festivals’ themes and programs are based on the preferences and needs
of locals (Skoultsos, 2014). Initially, this should not be approached as an obstacle to for
community involvement. However, as the current paper shows, there is a correlation between
efforts to connect the festival with the local tourism product and success of respective efforts
with the level of community involvement. To an extent, it can be argued, that the mentality of
festival managers to involve local community to the festival management and activities lead
to better results regarding positive tourism impacts. In other words, festivals that aim directly
to be included in the local tourism product should inevitably implement activities of engaging
locals to their activities and management. These findings comply with previous researches
which stated that decision making and in general participation in event-related activities may
increase the willingness of local to act as hosts in the future (Pappas, 2014; Pappas 2017).
5 Removed variable: V2. There is a differentiated pricing policy for locals or/and for repeat visitors.
33 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Regarding the hypotheses set at the beginning of the survey, H1 and H2 are verified
due to the results of factor and cluster analysis. Different factors were revealed together with
distinctive clusters of festivals. Finally, H3 is partly verified because several variables proved
to have strong correlation with the cluster categorization and as a result revealed clusters
include festivals with different attributes. Specifically, cluster 2 includes festivals with high
community involvement levels and specific characteristics (see section “characteristics of
revealed clusters”). The main outcome from the above results is that differences in mentality
of festival managers leads to different results regarding the success of the festival. Finally, it
should be mentioned that a wider idea of community is important in order to be more active to
increase community involvement.
6.1 Limitations
Predictably current research has several limitations. These limitations are related to the fact
that selected variables were derived from literature. It would be better to be derived through
further qualitative research to festival managers and local people. In this case, tested variables
would be adopted to specific attributes of Greek festivals.
6.2 Conclusions & future research
Results of current research are useful for festival managers in order to comprehend the
importance of community involvement. It has to be highlighted that community involvement
is a feature widely accepted as necessary for the festival’s success. Nevertheless, managers
participated in the survey declared that they don’t implement practices of community
involvement at a high level and consequently festivals are not successful in terms of
integration in the local tourism product. In general, festival managers should comprehend that
community involvement play a significant role to the tourism exploitation of a festival and
event planning should integrate local citizens to event-related activities and decision-making
processes.
7. Reference
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edition. Australia, Wiley, 2002
Arcodia, C. & Whitford, M. 'Festival Attendance and the Development of Social Capital'.
Journal of Convention & Event Tourism, 8(2), 2002, pp. 1-18.
Azara, I. and Crouch D. 'La Cavalcata Sarda: Performing identities in a contemporary
Sardinian festival' Chapter in Picard, D. and Robinson, M. (Eds) Festivals, Tourism
and Social Change: Remaking Worlds, Clevedon, Channel View Publications, 2006
(pp.32-46).
Bowdin, G., Allen, J., O’Toole, W., Harris, R. & McDonnell, I., Events Management, 3rd edn,
Elsevier Ltd, Oxford. 2011
Delamere, T.. Development of a scale to measure resident attitudes toward the social impacts
of community festivals: Part 2: Verification of the scale. Event Management, 7(1),
2001, pp. 25–38.
Delamere, T., Wankel, L., & Hinch, T. Development of a scale to measure resident attitudes
toward the social impacts of community festivals: Part 1: Item generation and
purification of the measure. Event Management, 7(1), 2001, pp. 11-24.
Dwyer, L., Mellor, R., Mistilis, N. & Mules, T., A framework for evaluating and forecasting
the impacts of special events in Yeoman, I, Robertson, M, Ali-Knight, J, Drummond,
S, & McMahon-Beattie, U(ed.) 2010(reprinted), Festival and Events Management, An
International arts and culture perspective, Elsevier Butterworth-Heinemann, Oxford.
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Fredline, E., Host Community Reactions to Major Sporting Events, The Gold Coast Indy and
the Australian Formula One Grand Prix in Melbourne, Thesis, Faculty of Commerce
and Management, Griffith University, 2000
Fredline, L., Jago L. & Deery, M., The development of a generic scale to measure the social
impacts of events, Event Management, 8(1), 2003, pp. 23-27 in Getz, D., Event
Studies, Theory, Research and Policy for Planned Events, Elsevier Ltd., Oxford. 2007
Getz, D., Event Studies, Theory, Research and Policy for Planned Events, Elsevier Ltd.,
Oxford. 2007
Gursoy, D., Kim, K., Uysal, M., Perceived impacts of festivals and special events by
organizers: an extension and validation, Tourism Management, 25, 2004, pp. 171–181.
Hall, C., Hallmark Tourist Events. Impacts, Management & Planning, John Wiley & Sons
Ltd, West Sussex, 1992
Mann, M. The community tourism guide. London: Earthscan in Rogers,P. & Anastasiadou, C.
(2011), Community Involvement in Festivals: Exploring Ways of Increasing Local
Participation, Event Management, 15, 2000, pp. 387–399
Mason, P. & Beaumont-Kerridge, J., Attitudes of visitors and residents to the impacts of the
2001 Sidmouth International Festival, Chapter in Yeoman, I, Robertson, M, Ali-
Knight, J, Drummond, S, & McMahon-Beattie, U(ed.), Festival and Events
Management, An International arts and culture perspective, Elsevier Butterworth-
Heinemann, Oxford. 2004 (pp.311-329)
Mason, P. & Cheyne, J. Resident attitudes to a tourism development, Annals of Tourism
Research, 27(2), 2000, pp. 391-411.
McCabe, S. “The Making of Community Identity through Historic Festive Practice: The Case
of Ashbourne Royal Shrovetide Football” Chapter in Picard, D. and Robinson, M.
(Eds) Festivals, Tourism and Social Change: Remaking Worlds, Clevedon, Channel
View Publications, 2006, pp.99-119
Moscardo, G. Analyzing the Role of Festivals and Events in Regional Development. Event
Management, 11(1-2), 2007, pp. 23-32.
Pappas, N. Hosting mega events: Londoners’ support of the 2012 Olympics, Journal of
Hospitality & Tourism Management, 21, 2014, pp.10–17.
Pappas, N. Pre- and Post evaluation of Residents’ Participation and Support of the 2012
London Olympics. Event Management, 21 (6), 2017, pp. 747-770.
Picard, D., & Robinson, M. (Eds.), Festivals, tourism and social change: Remaking worlds,
Channel View, Clevedon. 2006
Ridolfi, E., Pujol, D., Ippolito, A., Saradakou, E. & Luca, S., An Urban Political Ecology
approach to local development in fast-growing, tourism-specialized coastal cities.
TOURISMOS, 12 (1), 2017, pp.171-204
Rogers,P. & Anastasiadou, C., Community Involvement in Festivals: Exploring Ways of
Increasing Local Participation, Event Management, 15, 2011, pp. 387–399.
Sarantakou, E., Kontis, A., The Development of Enriched Mixtures of Cultural Tourism, for
the promotion of Greek Mature Destinations, TOURISMOS, 11 (2), 2016, pp. 262-
283
Sarantakou E., Tsartas P., Bonarou C., How New Technologies Influence the Perception of
Athens as a Tourist and Cultural Destination 2018,. In: Katsoni V., Velander K. (eds)
Innovative Approaches to Tourism and Leisure. Springer Proceedings in Business and
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Stamoulis Publications. (in Greek), 2005
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Skoultsos, S., Tsartas, P. "Event tourism: Statements and Questions about its impacts on rural
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cultural consumption and sustainability, 2016 chapter in: Editors: Andreopoulou, Z.,
Leandros, N., Quaranta, G., Salvia, R., Tourism and New Media, Publisher: Franco
Angeli, 2016 pp.26-34
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Harris, R. & McDonnell, I. Events Management, 3rd edn, Elsevier Ltd, Oxford. 2011
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 36
Employee training in Athens luxury hotels and its relation to job
efficiency and company loyalty
Abstract:
The aim of this study was to evaluate the level of satisfaction from the training provided by
Athens luxury hotels to their employees and its correlation with job satisfaction and company
commitment. For this we evaluated a total of 108 completed questionnaires using SPSS for
Windows. We found that the correlation between adequate training and job satisfaction was
quite high, with the employees demanding more complete, specialized and personalized
training programs. We also found that hotel employees are not satisfied with work
environment, financial benefits, reward policies and job recognition, this resulting in low
commitment to the company. Athens five star hotels should adjust human resources policy
accordingly in order to increase loyalty.
Key words: Job satisfaction, company loyalty, training programs, luxury hotels
Papageorgiou Athina1, Kikilia Ekaterini2 and Varelas Sotirios3
1 Papageorgiou Athina, Assistant Professor, University of West Attica, 2 Ag, Spyridonos Str., 12243 Egaleo,
Athens Greece. Email: [email protected] 2 Kikilia Ekaterini, Professor, University of West Attica, 2 Ag, Spyridonos Str., 12243 Egaleo, Athens Greece.
Email: [email protected] 3 Varelas Sotirios, Lecturer, Neapolis University, Paphos, 2 Danais Avenue, 8042 Paphos, Cyprus. Email:
37 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Introduction
Current highly competitive tourism business environment has significantly changed the way
tourism enterprises operate, as they are obliged to adopt novel techniques in strategic
management and performance measurement in order to meet both national and international
competition (Kaleka & Morgan 2017, Krishnamoorthy & D'Lima 2014).
In order to become competitive, tourism enterprises need to quickly respond to
external environment changes and strategic decisions that other similar tourism businesses
adopt, and also try to be one-step-ahead of their competitors. For this, self-assessment and
strategy improvements are needed in order to gain competitive advantages (Aguiar-Quintana
et al 2016, Krishnamoorthy & D'Lima, 2014). Among other measures, continuous training
and specialization of staff are of paramount importance, as they reflect stability, commitment
to quality and the ability to change, while enhances employee job satisfaction and
commitment to the company (Amirtharaj et al 2011, Strietska-Ilina & Tessaring 2005).
2. Aim
The aim of this study was to identify the degree of satisfaction that the employees of luxury
hotels of Athens gain from the various training systems applied and its correlation with job
satisfaction and company commitment.
3. Material and method
To meet the aims of this study we used a structured questionnaire. We firstly recorded
responders’ demographics (part one, “demographics”) and then asked details about applied
staff training programs (part two, “measures related to staff training”), i.e. continuous training
and re-training, program adequacy and the extent to which these procedures met the
responders’ needs and expectations. With the next set of questions (part three, “evaluation of
11 statements”) we asked responder’s opinion on eleven specific statements regarding their
training while with the final set (part four, “characteristics of training programs applied”), we
recorded employees’ opinion on job satisfaction, personal income sufficiency and hotel
rewards policies.
The reliability of the questionnaire was assessed using Cronbach alpha index. When
the index value is greater than 0.7 there is strong consistency in the sample and it should
therefore be considered reliable (Tavacol & Dennick 2011). In this study internal consistency
reliability for the "measures related to staff training" was found to be 0.869, for the
"evaluation of 11 statements" it was 0.850 and for the "characteristics of training programs
applied" was 0.938, indicating satisfactory levels of our questionnaire reliability.
The survey was conducted between January and March 2019. We presented the
questionnaire to human resources management of 23 five-star Athens hotels through Google
Forms. Participation was voluntary and anonymous. A total of 108 completed questionnaires
were obtained and analyzed using the 24th edition of the SPSS for Windows statistical
package.
4. Results
Responders’ demographics are presented in Table 1.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 38
Table 1: Responders’ demographics
n %
Sex Male 36 33,3
Female 72 66,7
Age (years) 18-25 24 22,2
26-35 37 34,3
36-45 27 25
46-55 19 17,6
56-65 1 0,9
over 65 0 0
Education High School 16 14,8
University 55 50,9
MSc 25 23,1
PhD 0 0
Other 12 11.1
Years of employment
at the Hotel
Less than 1 16 14,8
1-5 47 43,5
6-10 19 17,6
11-15 19 17,6
16-20 4 3,7
More than 20 3 2,8
Years of employment
Totally
Less than 1 6 1,5
1-5 34 31,5
6-10 19 17,6
11-15 31 28,7
16-20 8 7,4
More than 20 10 9,3
Contract Permanent 61 56,5
Seasonal 47 43,5
Job position General Manager 0 0
Human resources manager 1 0,9
Other department manager 14 13
Employee 88 81,5
Other 5 4,6
The vast majority of responders (95.4%) noted that their hotel offers some form of
staff training. When asked about their preferred method of training (a multi-answer question)
employers seem to prefer counseling by the instructor when a problem occurs (71.7%),
followed by advanced training on certain matters (67.3%), counseling with monitoring groups
(57.9%) and presentations by the department’s head (54.2%). Studied hotel managers
however seem to prefer on the job training (93.33%), followed by audiovisual training
(40.0%), lectures (26.66%) and training using the internet (20.0%), while computer assisted
training methods and apprenticeship are popular in only 13.33% and 6.66% of cases
respectively. Most employees (65.4%) stated that the department’s head is actively involved
in their training while in only 10% of cases the department’s head is absent. When asked
about their satisfaction from the training provided, responders’ views were divided: 54% of
them stated that they do not undergo sufficient training to be effective in their job, while
43.9% were satisfied. Overall, and in contrast to the previous answers, training provided
39 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
seems to meet the expectations of almost half of the participants (45.8%), while 25% of them
disagree.
Responders were then asked if they are familiar with the overall strategy of their
company and 72.9% gave a positive answer. When asked about their salary, 71% stated that
they are not satisfied, while only 40% agree that their company’s reward policy is
satisfactory. Also, only 30% of responders stated that their work is fully recognized by their
superiors.
When asked about their personal life, only 22.5% of responders stated that they are
satisfied, while 46% find it difficult to achieve a satisfactory combination of work and
personal life. Communication between the employees also seems to be unsatisfactory, as only
2% of responders stated that they communicate well with their colleagues and 86.9% do not.
Overall, only 47.6% of responders stated that they are satisfied from their work; however
88.8% of them would like to be a client of their hotel.
When asked to evaluate the educational programs implemented by their company (a
multi-answer question), responders stated that the majority of educational programs are job-
related (58.5%) and valuable (54.2%). In addition, 46.7% were satisfied with the possibility of
acquiring new knowledge, while the majority of staff training programs were moderately or
not at all satisfactory, as they did not contribute to retention (76.6%), efficient use of time
(76.6%) and enhancing personal growth (74.8%), with the latter being particularly
contradictory to previous answers.
Table 2: Characteristics of training programs
0% 20% 40% 60% 80% 100%
Practical value
Plenitude of training
Aquiring new knowledge
Personal enhancement
Relevance to the job
Effective time use
Interest maintenance
Clarity
Characteristics of training programs and level of satisfaction
None Limited Average High Very high n.a.
We then cross-tested:
The effect of certain demographic variables on the response of hotel employees regarding
training programs and company loyalty. To evaluate this we used gender, type of
employment (permanent or seasonal), total years of service, age and the educational level
of participants as independent variables.
The effect of years of service against the “eleven statements” group, sub-divided into two
groups, job satisfaction and education.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 40
Demographics against employees' views on the usefulness of applied staff training
measures.
Any relationship between demographics and respondents' perceptions on certain
characteristics of the educational programs: practical value, completeness of training,
enhancement of personal development, relevance to employment, efficient use of time,
maintenance of interest and clarity.
Regarding “sex” and “overall job satisfaction”, t-test showed no difference (t = -1.505,
df = 105, p = .135) and the same was true for “education level” (t = -1.268, df = 105, p =
.208). On the contrary, women seem to experience a greater “lack of recognition from their
superiors” (t = -2.052, df = 105, p = .043) than men.
When analyzing participants' views on the usefulness of implemented specific
measures related to staff training, we found statistically significant differences in favor of
women in two statements, "Discussion with monitoring groups, to share experiences in
implementing ideas" (t = 2.252, df = 58.508, p = .028) and "Summary presentation of current
issues" (t = 2.057, df = 105, p = .042).
Applying t-test on job satisfaction among permanent or seasonal employees we found
a statistically significant difference between employees' satisfaction and their employment
status (t = -2.510 df = 105, p = .014) as seasonal employees were less satisfied.
Participants' views on the usefulness of the training they received were unaffected by
their employment status (t = -1.500, df = 105, p = .137), while a marginal statistically
significant difference was seen in the responses to "Completeness of training" (t = 2.011, df =
105, p = .045) with permanent employees showing a higher degree of satisfaction. The effect
of work experience on participants' responses was tested by one-way independent sample
analysis of variance (ANOVA, Ostertagova & Ostertag 2013). Participants were divided into
six year-of-service groups, but no statistically significant difference (p > 0.05) was found
between employees’ satisfaction and years of service [F (2.213) = 1.451, p = .213 > .05, n 2 =
.067]. The same was true for the relationship between the service groups and the employees'
views on the plenitude of the training course [F (1.257) = .389, p = .855 > .05, n 2 = .019].
Using the ANOVA test for the same groups in relation to the statement "I know the
overall strategy of the company ", employees with fewer years on the job know less about the
business strategy [F (2.915) = 4.488, p = .001 (p < .05)]. In relation to the proposal "My
income is satisfactory", those with at least 20 years of service agree more than employees
having 1-10 years of experience, who strongly disagree [F (3.339) = 4.458, p = .001 (p <
.05)]. Finally, in relation to the statement "In my work I receive the recognition that I
deserve", those with 1-15 years of service fully disagree [F (2.200) = 2.861, p = .019 (p <
.05)].
The age of the participants (same distribution as before) against job satisfaction was
another independent variable tested using the ANOVA test. It did not show any statistically
significant correlation between age and job satisfaction [F (1.926) = 1.580, p = .185 > .05, n 2
= .058] or education [F (1.948) = .770, p = .547> .05, η 2 = .029]. We did not perform any
post-hoc test, as there were not enough participants in these age groups, this being a limitation
of this study. In contrast, we identified statistically significant differences when examining the
relationship between age and the proposal "I know the overall strategy of the company", [F
(2.019) = 2.857, p = .027 (p < .05)], "My income is satisfactory" [F (2.523) = 3.128, p = .018
(p < .05)], "In my work I receive the recognition that I deserve" [F (2.018) = 2.554, p = .043
(p < .05)] and "There is a good balance between my professional and personal life" [F (2.423)
= 3.002, p = .022 (p < .05)].
We then checked whether the educational level of the employees involved in the
research influenced their views. The ANOVA test did not show statistically significant
differences for the dependent variables used, as for training the results were F (2.324) = .924,
p = .453 (p > .05), n 2 = .035 and for satisfaction F (2 .526) = .413, p = .799 (p > .05), η 2 =
41 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
.016. Therefore, employees' views on the adequacy of the training they receive, as well as
their job satisfaction, are not affected by their educational level.
To test if employee’s work commitment is influenced by the training they receive, we
used Pearson's coefficient r test (Sedgwick 2012). The analysis showed a moderately positive
correlation r = 0.497 that was statistically significant (p < .05) for the proposals "Overall, I am
satisfied with my work" and "I receive sufficient training to be effective in my work".
Similar results emerged from the correlation of the responds on the proposals
"Overall, I am satisfied with my work in the business" and "The training provided by
management is desirable and fulfills my expectations". The coefficient r = 0.475 indicates a
moderately positive correlation (p < 0.05) between the employees' work satisfaction and their
view on training provided (i.e. if it is desirable and fulfills their expectations), as seen in Table
3.
Table 3: The relation between the satisfaction from the job and the satisfaction from the
training programs
Completely
agree
Rather
agree
Not agree
or disagree
Rather
disagree
Completely
disagree
Satisfaction from the job 3.7 40.2 27.1 27.1 1.9
Satisfaction from training 3.7 43.9 27.1 24.3 0.9
0
5
10
15
20
25
30
35
40
45
50
Satisfaction from the job and the training programs
Satisfaction from the job Satisfaction from training
5. Discussion
Modern tourism enterprises, in order to make managerial decisions regarding staff training,
need to perform well-structured periodic staff evaluations in order to apply novel methods for
improving employee performance through training and specialization (Alomari et al 2017,
Haynes & Fryer 2000). This evaluation provides information useful to define clear and
objective goals and develop certain actions to achieve these goals, including adequate training
methods for the employees (Ashton 2017, Aguiar-Quintana et al 2016, Krishnamoorthy &
D'Lima 2014).
This study investigated whether appropriate training is associated with job satisfaction
and business loyalty. Results showed that the vast majority of five-star hotels in Athens
(95.4%) provide some kind of training that is addressed to 90.7% of employees. The
preferred method is on-the-job-training, probably because it is job-related and cost-effective,
as compared to other methods, i.e. audiovisual or computer related and apprenticeship.
Responders on the other hand seem to prefer counseling (71.7%), as it provides clear
answers, reduce work stress and fully support them. Upgraded training in specific topics also
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 42
appears popular (67.3%), reflecting their need to approach issues quickly and thoroughly,
while brief presentations on topics of interest is another strong option (54.2%).
We also found that hotel employees are not completely satisfied with both their work
environment and financial benefits a finding that is consistent with other studies (Dadeer et al
2017, Chi & Gursoy 2009). Tourism industry, although offering career opportunities even in
times of economic crisis, cannot provide high salaries, except for very few high-level jobs.
Employees state however that they are familiar with the company strategy, a finding that
shows that there is a good communication between them and hotel administration. This is
very important for job satisfaction, employee commitment and employee productivity (Anku
et al 2018, Bhatti & Qureshi 2007).
Responders state that the reward policies implemented by the company are not
satisfactory and do not meet their expectations, while they also think that they do not receive
the recognition that they deserve (60% in both cases). It is possible that hotels do not see
motivation as a priority in order to urge their employees to achieve higher goals than the set
ones (Putra et al 2017). It is also likely that this is related to the particularly high rate of staff
change (new recruitments) seen in hotels, as many prefer to hire new staff rather than leverage
existing ones in different positions (Solnet et al 2019, Anku et al 2018, Lertwannawit et al
2009).
The inability to achieve a balance between professional and personal live is a worrying
finding. Unstable working hours, shifts, days off when it suits the hotel and not the employee
and working on public holidays are probably contributing to this (Paek et al 2015, Bednarska
2013). As a result, hotel employees find it difficult to socialize and keep pace with their
family or friends.
In addition, several issues regarding employee intra-communication were identified, as
only 13% of respondents stated that such a communication was satisfactory. The positive
work climate, largely shaped by the communication between employees, is a key factor for
employee loyalty (Matzler & Renzl 2006). Our findings probably result from high
competition between colleagues, work under pressure and bad working conditions, including
work environment issues (Dardeer et al 2017). Also in many cases hotel staff does not see a
department issue as an overall business problem, perceiving themselves firstly as department
members. It is worth noting, however, that 48% of respondents stated that they were satisfied
with their job, while 9 out of 10 would like to be clients of the hotel they work, probably due
to the high quality of service five star hotels offer.
Regarding education, several important findings were revealed. Firstly, 65% of
responders stated that their supervisor is actively involved in improving their work and
training. It seems that communication between the supervisor and the employees is extremely
important in team work and also confirms the previous finding that the hotel management
prefers on-job training by the supervisor.
The answer to whether the training that employees receive in order to be effective in
their work is sufficient was inconclusive. 44% of responders stated that they find it effective,
27% "neither agree nor disagree", and 27% disagreed with the proposal. This result could
reflect the personality of the employees and the degree to which everyone trusts himself or
herself. It might also be affected by work experience, as un-experienced employees definitely
seek more training programs (UNWTOa 2020).
The evaluation of the educational programs gives us some important findings
regarding the quality of these programs. Employees stated that about half of the educational
programs organized by their hotels are job-related, has a practical value and offers the
potential to acquire new knowledge. Also, four out of ten employees seem satisfied with the
programs, regarding completeness and clarity. On the contrary, these programs seem to fail to
maintain interest, efficient time use and personal development enhancement, as almost eight
out of ten employees were not satisfied when asked about these parameters.
43 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
The evaluation of the educational programs applied is important for hotels, as their
quality and efficiency must always be tested. About half of the responders find these
programs to be job-related, of practical value and effective in providing new knowledge,
while four out of ten employees appear satisfied with the programs in terms of completeness
and clarity. However almost 80% of responders think that they do not maintain interest, are
not time consuming and do not lead to personal development. It seems that the organizers of
these educational programs emphasize on the content rather than their presentation and
personalization. The programs are relevant and useful, but not attractive to all. This may be
due to limited time and resources or the use of widely used programs that are not tailored to
meet the needs of each particular hotel or department. Low levels of employee satisfaction
mean that the content and specificity of these programs need to be redesigned. UNWTO aims
to solve this problem by providing the TedQual Certification System that is composed of
several evaluation criteria that are universally applicable to tourism education, training and
research programs aiming to measure the effectiveness of the pedagogical system and
evaluate to which extent the needs of the certain tourism sector are covered (UNWTOb 2020).
Regarding sex, it seems that it does not affect company loyalty and overall satisfaction
of applied training programs, but affects women’s impression on certain methods of training
and also job recognition. Indeed, in our study women seem to make greater efforts to be
recognized in their work than men, while consultation with their supervisors or monitoring
groups on various everyday issues is not considered to be practical and useful to women
employees.
Regarding work status (permanent or seasonal) it did not strongly affect responders’
view on the training programs offered. No differences were seen as for the usefulness of
training, while employees with permanent positions are more satisfied that seasonal working
responders. This could be explained by the fact that seasonal staff may not have the same
amount of training time as the permanent staff, thus considering training programs
incomplete. On the contrary, seasonal hotel workers are much less satisfied with their work
than permanent employees, probably due to professional uncertainty, high work load and
constant working pressure.
Regarding the years of service, it did not affect job satisfaction but several
discrepancies were seen on various other issues. Participants with fewer years of service do
not have a good understanding of the company strategy, as do employees with more work
experience in the hotel, who appear to be more familiar with the company's goals. The same
was true regarding income and job recognition, as seasonal personnel has lower salaries and
do not get jobs requiring high responsibility and expertise. Combining age and years of
service, older employees are more familiar with the overall strategy of the business than the
younger ones, with the latter being less satisfied with their income and job recognition,
probably because they do not hold positions of responsibility and do not get promoted as
quickly as they expect. Another interesting finding is that the age group reporting most
dissatisfied with the balance between work and personal life is the middle age group (36-55
years), probably because at this age family is a very important aspect of their life, resulting in
an imbalance between professional and personal time (Bednarska 2013).
Regarding the level of education, it did not affect responders’ views in general, since
neither the questions related to the evaluation of educational programs nor the questions on
job satisfaction showed any significant differences between the various levels of employees’
education.
Finally, job satisfaction is mildly associated with the satisfaction they receive from
training, as 43.9% of participants who stated that they are satisfied with their training are also
satisfied with their job. This probably means that adequate and specific training may lead to
higher levels of job satisfaction.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 44
In summary, this study proved the necessity of quality staff training programs, as the
vast majority of participants see training as a necessary precondition for a highly satisfactory
job performance. The first key question of this research on the relationship between adequate
training and job satisfaction was positively answered, as the correlation between these two
factors was found to be quite high, despite the fact that employees showed skepticism
regarding the training programs offered, demanding more complete, more specialized and
more personalized ones. The second key question however was not positively answered, as
hotel employees are not satisfied with the work environment, financial benefits, reward
policies and job recognition by their superiors. This means that Athens five star hotels, in
order to increase loyalty, should adjust their human resources policy accordingly.
Future research could compare luxury hotels operating in Attica and other areas, both
in Greece and abroad and also compare 5 and 4/3 star hotels performance, in order to identify
areas for further improvement.
6. References
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and Quality Management in the Tourism Sector (Case Study of Human Resources
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Aguiar-Quintana, T., Moreno-Gil, S, Picazo-Peral, P. (2016). How could traditional travel
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Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 46
Sharing economy in time of economic crisis: The owners' perspective of
Airbnb rentals in Greek cities
Abstract:
This paper focuses on the impacts that sharing economy has on the life of Airbnb rental
owners based on a primary research to Greek cities and destinations. Firstly, the current paper
presents the theoretical background of sharing economy and P2P business models and
presents secondary data for the relative Greek market. The primary data of this paper were
gathered through an online questionnaire which was delivered to owners of Airbnb house
rentals and discuss their perspective of the socioeconomic changes that sharing economy has
to their own lives. The results showed that there are certain reasons due to which the owners
decided or were “actuated” to join the Airbnb platform, such as financial crisis and income
opportunities, rental taxation etc. Owners argued that there are various positive
socioeconomic impacts that highlight the importance of sharing economy to local societies:
increased income, economic opportunities, enhanced opportunities for travelling (demand
side), additional demand for local businesses and so on. The current paper argues that there
are specific characteristics for each society that should be considered to examine positive and
negative aspects of sharing economy impacts and decide which policy is the most appropriate
for each destination.
Keywords: Sharing economy, Airbnb rentals, Airbnb Owners’, Greece
Sofoklis Skoultsos1, Anna Kyriakaki2, Alexios – Patapios Kontis3, and Despina Sdrali4
1 Corresponding-Address: Sofoklis Skoultsos, Department of Tourism Economics and Management, University
of the Aegean, 8, Michalon Str., Chios, Greec. Email: [email protected] 2 Corresponding-Address: Anna Kyriakaki, Academic Faculty lab Instructor (PhD), Business School, University
of the Aegean. Email: [email protected] 3 Corresponding-Address: Alexios – Patapios Kontis, Department of Tourism Economics and Management,
University of the Aegean. Email: [email protected] 4 Corresponding-Address: Despina Sdrali, Assistant Professor, Department of Home Economics and Ecology,
Harokopio University. Email: [email protected]
47 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Introduction
In recent years, technology innovation and supply-side flexibility have created a growing
interest in sharing economy (Zervas et al., 2017). Sharing economy as an alternative and
highly flexible economic model allows people to obtain, give and share access to products and
services, coordinated through community-based online services (Hamari et al., 2016). Since
the later part of the last decade, travel and tourism are at the forefront of the sharing economy
and many tourism related activities, such as accommodation, transportation and
entertainment, are offered through sharing economy platforms (Skoultsos et al., 2017).
The strengthening of the tourism industry, the increase of arrivals and overnight stays,
and the economic crisis as well, have boosted the sharing economy. On the other hand,
tourists are more open to self-guided holidays (OECD, 2016). They use -even elderly ones-
technology advances and seek for information from social surrounding or anonymous tourists
who post on the internet. Furthermore, tourists have rethought their values, lifestyles and
patterns of consumption (Sdrali et al., 2015). They are seeking to push the boundaries of their
comfort zone, searching for authentic vacation and an involvement and interaction with local
people (Tsartas et al., 2017). Sharing economy platforms have been thus promoted as
opportunities for customization of the experience, for “meeting” the locals and for authentic
experience that are different from the traditional tourism product (Sarantakou et al., 2018;
Juul, 2017).
In addition, sharing economy has received a great deal of attention by the potential
entrepreneurs due to the economic crisis and its consequences (such as unemployment,
decreased income, inequality, poverty etc.), which opened up opportunities for new forms of
employment.
One of the most discussed examples of the sharing economy is Airbnb; a popular
online marketplace for short-term rentals which was founded in 2008 and since then it has
spread quickly. As a result, various researchers focused their interest to enlighten all the
different aspects of this new type of businesses and examined specific services and sharing
economy platforms (e.g. Airbnb). The most research has been conducted to investigate why
tourists choose to stay in Airbnb accommodation and explore the ways they use the service
(e.g. Farmaki and Stergiou, 2019; Stollery and Jun, 2017; Guttentag, 2015). Researches
showed that customers choose these types of services based on a wide range of reasons such
as: lower prices, increased alternative choices, enhanced experiences (e.g. living like a local),
etc. Other researchers focused on the impacts that P2P models have on the operation of
traditional businesses. For example, they try to reveal the impacts that short term rentals have
on the operation of hotels and destinations. However, limited research has been conducted
regarding the impacts on the life of suppliers of sharing economy services and their own
perspective on this new business models.
This paper aims to study and analyze the socio-economic profile and the basic reasons that the
individuals rent theirs homes via Airbnb platform but also their perceptions about social and
economic impacts that sharing economy has on based on a primary quantitative research to
several cities and destinations in Greece.
2. Literature Review
2.1 The rise of sharing economy
Rauch and Schleicher (2015) claim that the modern sharing economy has two features, based
on the idea that it may be monetized (e.g. earning income from sharing assets) or non-
monetized (e.g. swapping or gifting platforms). According to Szabó (2017), sharing has two
forms; the “pure sharing”, which works without any profit or business consideration, and the
mixed version of sharing, which uses the potential of community, being driven by business
interest from the intermediary’s side.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 48
The sharing economy has opened up new opportunities for the providers and the
consumers as well. The sharing economy platforms have seen huge growth which is due to a
number of parameters, such as technological, economic and social.
Specifically, the speed and adoption of technological innovation has a considerable
impact on the aspects of our lives, such as communication, production and distribution
(Kontis et al., 2019; Oskam and Boswijk, 2016; Katsoni, 2016; Fountoulaki et al., 2015;
Kavoura and Katsoni, 2013). People have become familiar with the internet and especially
younger generation has steadily become more comfortable with purchasing goods and
services online. Mobile devices have equipped with applications that make people searching
for and accessing the available guest room, car, parking space or home-cooked meal even
from people they have never met. People share and trade their own goods, becoming
producers/suppliers and sellers without many times having the use of money (Sigala, 2017).
For Gansky (2010), the sharing economy benefits refer to the “triple bottom line”
included a greener commerce, greater profits and rich social experiences. However, economic
benefits may be considered as the strongest driver of the sharing economy. The sharing
economy is able to contribute to economic development, create new jobs, support jobs in
other industries, generate new income resources and give the individuals the capability of
micro-entrepreneurship.
Sharing aims at goods and services which would be otherwise unaffordable for the average
consumer (Szabó, 2017), becoming less dependent on ownership (Skoultsos et al., 2017;
Frenken and Schor, 2017). Participating in the sharing economy platforms can maximize the
users’ utility as they can choose lower-cost options (Zervas, et al., 2017; Belk, 2010;
Lamberton and Randall, 2012). Recent research has shown that people with low income are
the ones who mainly benefit from the sharing economy (Bradshaw, 2015; Fraiberger &
Sundararajan, 2015; Kodransky & Lewenstein, 2014). However, for Chiang (2015) people
who use sharing economy services seem to be “affluent”.
Moreover, there are many “green” sharing examples, such as carpooling, ride-hailing,
bike-sharing and exchanging used clothing, that produce fewer goods to deliver value to users
(Voytenko et al., 2016; Schor and Wengronowitz, 2017; Sigala, 2017). However, at the same
time, an opposite effect is generated (Szabó, 2017). According to Schor (2014) and Szabó
(2017), accommodation and transportation sharing services cannot always lead to a reduction
of carbon emissions, and the environmental impact may be increased. Why? The users are
travelling more often than before, and the traffic jams are increasing. Thus, the environmental
effects of the sharing economy platforms are seemed complex (Kontis et al., 2020; Sarantakou
et al., 2019; Frenken and Schor, 2017; Douglas & Lubbe, 2014; Kontis, 2014; Berne, et al.,
2012).
Another reason why individuals join sharing platforms is “social capital” (Botsman and
Rogers, 2010). The interested parties are allowed to meet new people, and may make friends,
share their culture and gain inter-cultural experiences (Farmaki and Stergiou, 2019; Böcker
and Meelen, 2016). However, the increasing number of people motivated by economic
reasons and the quality of ratings may contribute to the declining importance of social ties on
the sharing economy platforms (Frenken and Schor, 2017).
Sharing entails a high degree of risk due to the information asymmetries. Therefore,
trust seems to be the cornerstone of the sharing platforms and the base among its users
(Szabó, 2017). According to the PwC report (2015), the sharing economy is referred as “the
trust economy”, and for Slee (2013), the two main aspects of sharing economy are
coordination and trust. For this reason, the digital platforms, through rating and reputation
systems, are able to make sharing less risky and more appealing (Frenken and Schor, 2017).
However, according to Overgoor et al. (2012) and Zervas et al. (2017), ratings are considered
inflated and not very accurate. Ma et al. (2017), having examined how hosts describe
themselves on their Airbnb profile pages, found that they use a variety of disclosure strategies
49 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
which cause differences in perceived trustworthiness scores. The findings suggested that
longer self-descriptions and a mix of assessment signals in combination with conventional
ones that provide information about one’s hospitality or interests, are perceived to be more
trustworthy.
Concluding, despite the positive impacts of the sharing economy, it is argued that it
may display problems as well, regarding the safety and insurance issues, the establishing trust
and lack of information asymmetry, and environmental impacts (European Parliament’s
Committee on Transport and Tourism, 2015).
2.2 The sharing economy in the tourism sector. The example of Airbnb
The strengthening of the tourism industry, the increase of arrivals and overnight stays, and the
economic crisis as well, have boosted the sharing economy. According to OECD (2016), the
sharing economy is forecast to reach USD 335 billion by 2025. Much of this growth is in the
tourism sector and especially in the following four sub-sectors of it; i.e. accommodation,
transportation, dining and travel planning.
It is worth mentioning that short-term rental services within the sharing economy are
no longer regarded as alternative ones, but a widespread choice (Quinby, 2016). The
European Association of Hotels and Cafes estimates that in Europe the size of the sharing
economy accommodation is double than the size of the traditional hotel accommodation. A
typical example is France, where 40% of the available accommodation is available through
the sharing economy platforms (European Commission, 2016).
One of the most discussed examples of the sharing economy accommodation is
Airbnb.com. According to the website of Airbnb (2020), it has 7 million listings in 220
countries worldwide, while in 2008 -the year of establishment- it had 1.5 million listings in
190 countries worldwide. Airbnb also accounts for a similar number of room nights as some
major hotel brands (Guttentag, 2015). Furthermore, it was valued at 31 billion U.S. dollars in
2017 (25.5 in 2015), with total equity funding of around 3.3 billion U.S. dollars (2.3 in 2015).
Airbnb create opportunities for local people to rent their home for short stays and
generate additional income or/and support them to explore new business ventures (Kontis, et
al., 2018). For example, Airbnb hosts in Australia earned a median income of $4,920 in 2015-
16; a supplement to a household’s main sources of income, which may be handy for living
expenses, to pay down debt or increase savings.
In addition, despite the lack of official data, Airbnb can provide benefits to local
communities, as the Airbnb guests use to spend money in the area where they stay, rather than
in areas which traditionally benefit from tourism. With the majority of Airbnb
accommodation situated outside major hotel districts and nearby local neighborhoods,
travelers are likely to visit restaurants, bars, attractions and shops in the area where they stay.
Thus, a range of local businesses is enhanced.
Moreover, tourists are able to live like a local, staying at a host’s private space and
using services in a local neighborhood. Vacation, through the Airbnb platform, can be made
more “authentic”. The guests are allowed to meet a real neighborhood and local people and
enjoy a personal connection with their host and the surrounding community. According to
Sigala (2017), the experience of domesticity and sociality may represent a stronger driver for
using collaborative commerce, as the feelings produced are something that no one can get in
the traditional tourism industry. Furthermore, Airbnb gives the guests the opportunity to
decide what to visit and do under the direction of the local hosts, in order to “live like a local”
(Paulauskaite, et al., 2017).
On the other hand, Airbnb hosts enjoy a number of benefits arising from their
activities on the platform. These benefits are not limited to the income earned from the Airbnb
stays. The hosts also benefit from the interactions with their guests and the broader
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 50
community and can experience new cultures without leaving their hometown. Schor (2015)
found that half of the Airbnb hosts were motivated by social interaction and socialized with
their guests. In addition, Ladegaard (2018) showed that socially oriented hosts from Boston
were eager to interact with foreign guests who were different enough to be interesting and
similar enough to be comfortable as well.
Platforms like Airbnb connect people and this personal connection can range from the
mere exchange of services to a conversation or lasting friendship. The ability of Airbnb to
facilitate social interactions as well as accommodation is a key benefit of the platform.
However, Airbnb is considered “guilty” for increasing competition amongst the
traditional accommodation establishments and the sharing ones and creating property
conflicts amongst the local residents (Stergiou and Farmaki, 2019; Gutiérrez et al., 2017)
causing fears of rising rents (Avdimiotis and Poulaki, 2019) and property prices. At last but
not least, it is argued that Airbnb may display problems regarding peer-to-peer discrimination
(Ge et al., 2016), and less employment for lower-educated blue and pink collar workers
(economic inequality) and lower earnings for related markets, while neighbours may also
experience nuisance and feelings of danger from strangers (Frenken and Shor, 2017).
2.3 How to organize an Airbnb
Customer segments: Airbnb is a marketplace where travelers (guests) and locals who have a
shareable space (hosts) are connected around the world. Airbnb hosts offer their properties for
rent for days, weeks or months, and Airbnb guests can search for and book any of these
properties, subject to host approval (Zervas et al., 2017). People who want to become Airbnb
hosts can offer a whole house or a private room or a shared room.
The process: The hosts can list their space on Airbnb at no charge and upload
personal characteristics and information on their place, the number of people that it can
accommodate, the amenities it offers, its price, its availability, and photos and a map showing
the approximate location. Then, the search for the guests follows via the website’s tools. A
guest seeking to rent a property on Airbnb can view the desired destination and dates and can
browse by price range and size of the property. Geographical neighborhoods, amenities, host
language and room types can be some other criteria. Upon finding a space, a request is sent.
Airbnb presents the guest’s request to the host who accepts or declines it, and after the
booking is made, Airbnb charges both the hosts and the guests.
Key element: Trust is the key element of the sharing economy. According to Zervas
et al., (2017), trust is difficult enough to be built due to the information asymmetries the users
face. This happens because the guests and the hosts typically know little about each other.
Thus, Airbnb, in order to build trust among its participants, beyond self-supplied information,
encourages them to verify their identity. The users can do so by linking their Airbnb account
with other website accounts (e.g., Facebook, LinkedIn), and by providing a working email
address and phone number, and a copy of their passport or driver’s license. Moreover, once
the guest completes his/her trip, both the host and the guest are allowed for 14 days to review
and rate, on a scale from one to five stars, each other on the Airbnb website.
Airbnb in Greece: The new business model, in which digital platforms create an open
market for temporary use of goods or services, mainly provided by individuals, has recorded
during the last decade rapid growth also in Greece within the sharing economy. As in other
destinations, sharing economy model extends to a spectrum of business sectors, among which
the most developed in Greece is that of private short-term accommodations through digital.
The familiarization with social networks, the wide use of online markets and electronic
services such as the expansion of mobile devices and the increasing access of Greeks to the
Internet are some of the main factors for the development of the sharing economy and related
web-based electronic platforms and mobile applications. In Greece there is a number of short-
51 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
term rental digital platforms, such as Airbnb, TripAdvisor, Booking.com, HomeAway,
HouseTrip, Flipkey, Trivago, 9Flats, Roomorama, Stay in Athens and trip2Athens.
The worldwide rapid growth of sharing economy found the majority of public
authorities unprepared. The legal initiatives that were undertaken during the development of
the “sharing economy” phenomenon have resulted in wide variation in the legislation
governing the operation of short-term rentals between countries or specific destinations. The
expansion of short-term rentals and the reactions of established Greek tourism stakeholders
have showed up the need for an explicit institutional demarcation and operating framework,
ensuring equal competitions terms between new and traditional tourism providers. The Greek
parliament, in order to regulate key issues of this new market such as tax evasion and safe and
quality provision of services by unlicensed operators, has made a series of legislative
interventions (Laws 4179/2013, 4336/2015, 4446/2016, and 4472/2017), whose results will be
visible over time. The long-lasting lack of a relevant institutional framework and the gradual
implementation of recent laws allowed the establishment of an efficient and appropriate
framework for official registration of short-term rentals just in last period. As consequently
precise data on the evolution of listed properties and short-term rentals sizes listed properties
were not available from official sources (official authorities and bodies).
Based on data from private international database AirDNA (Table1), total active
rentals in Greece that distributed via share economy platforms ware 132 in 2010 and arise to
126.231 at the middle of 2018 (increasing 956 times or 95.630%).
Table 1: Total number of listed short-term rentals in Greece, 2010-2018
Year Total of active rentals Annual increase % Annual increase
2010 132
2011 747 615 466%
2012 2.298 1.551 208%
2013 5.390 3.092 135%
2014 12.063 6.673 124%
2015 26.455 14.392 119%
2016 57.307 30.852 117%
2017 96.217 38.910 68%
2018* 126.231 30.014 31%
Source: www.airdna.co, Athanasiou & Kotsi (2018)
* The data for 2018 refer to the end of the first half of the year. Every property in Greece
is covered from October 2016 onwards
Αs expected, tourism destinations across the country with the largest tourist flows
attract the majority of active accommodations via share economy platforms. In 2018 five
regions of the country (Attica, South Aegean, Crete, Central Macedonia and Ionia Islands)
possess over of 80% of the total number of listings properties distributed via share economy
platforms (Table 2)
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 52
Table 2: Listed short-term rentals in Greece by region, 2010-2018
Source: www.airdna.co, Athanasiou & Kotsi (2018)
* The data for 2018 refer to the end of the first half of the year. Every property in Greece is
covered from October 2016 onwards
The expected benefits and the enthusiasm of independent micro-entrepreneurs have led to
frenetic growth rates with insufficient time period and limited information for the
sustainability of these investments.
Table 3: Facts for Airbnb in Greece, 2017-2018
Metric 12/2017 12/2018 Growth Rate
Available Entire Place Listings 59,379 72,144 21%
Booked Entire Place Listings 17,138 22,079 29%
Listed Nights 473,163 585,766 24%
Booked Nights 249,577 270,021 8%
Occupancy 52.7% 46.1% -13%
Average Daily Rate €152.96 €126.44 -17%
RevPAR €80.68 €58.28 -28%
Source: www.airdna.com
According the report of Mark Saltana (AirDNA, 2019) diverging trends in some of the
key performance indicators of short-term leases through Airbnb were shaped. On the one
hand there has been an increase in both "booked nights" and "total listings properties", but on
the other hand there has been a decrease in all short-term rental metrics such as Occupancy,
Average Daily Rate (ADR), and Revenue Per Available Rental (RevPAR). Despite the
increase in demand (booked nights +8%), the increase of supply, which surpass the increase
in demand (Available Entire Place Listings +21% & Booked Entire Place Listings +29%)
results in increased competition and leads to both lower occupancy and lower prices (ADR
and RevPAR).
53 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
3. Research Methodology
This paper aims at studying and analyzing the impacts that sharing economy has on the life of
Airbnb rental owners based on a primary quantitative research to Greek cities and
destinations. More specifically, the main survey aims are the following:
1. the determination of the demographic characteristics of the Airbnb houses owners (e.g.
age, income, education, etc.) and of the general characteristics of the Airbnb houses in
Greece (e.g. houses’ location, years of cooperation with the Airbnb, etc.),
2. the identification of certain reasons due to which the owners decided or were
“motivated” to join the Airbnb platform (e.g. financial crisis, income opportunities,
rental taxation etc.),
3. the investigation of the personal impacts (economic and social) that the sharing
economy (especially Airbnb) has both on the life of Airbnb rental owners and in
general ways,
4. the investigation of the key factors that influence the owners’ perceptions and attitudes
towards the legislative framework but also the impacts (social and economic) of
sharing economy and specifically of Airbnb.
4. Sample and data collection
For achieving the above goals, a primary quantitative research was undertaken by means of a
structured questionnaire. The research focused on a representative sample of 218 Airbnb
rental owners. Research was conducted via e-mail questionnaires sent to Greek owners
Airbnb houses, from May 2018 to December 2018. Taking into consideration the figures of
the population and the research objectives, the purposive sampling method was applied as this
method is widely used, mainly because of its simplicity in terms of statistical inference
(Iosifidis, 2017). According to the aims of the research, individuals/owners from different
Greek destination/region, belonging to both sexes and exercising diverse professions etc., are
included so as to guarantee sample representativeness (Levy & Lemeshow, 2013; Iosifidis,
2017). The distribution of rental houses of Airbnb in the sample almost follows the allocation
of hotel beds per region, with the regions of Attica and Central Macedonia being superior
because of the existence of the largest urban centers (Athens and Thessaloniki, respectively)
of Greece (see Table 4).
4.1 Survey instrument
To collect the research data was used an e-questionnaire with totally 28 close-ended questions
(five-point Likert scale, multiple choice true/false, and general multiple-choice ones). The
researchers draw from research aims and previous researches for the formulation of the
questions (Boswijk, 2016; Guttentag, 2015; Zervas et al., 2017). The questionnaire consisted
of five separate sections. The first section analyzed the “Demographic Profile or the
Respondents”, the second was about “General Characteristics of Airbnb houses”, the third and
fourth section covered the “Economic impacts of Airbnb” and the “Social impacts of Airbnb”,
respectively, and the fifth section consisted the “Attitudes of legislate framework about
Airbnb”. The questionnaire was available in Greek language. The statistics package SPSS 24
was used for the processing and the analysis of the data.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 54
Table 4: Geographical distribution of the Sample (Greek owners Airbnb houses)
5. Results & Discussion
5.1 Demographics of the owners
Regarding age of the participants in the survey, most of them are between 36 to 55 years old
(~60% of the sample). Also, it has to be noted that there is a significant percentage from 26-
35 years old (23.9%) which is the age that has been affected from the financial crisis the most.
Also, 36.4% of the sample have an annual income between 10.000 – 20000 euros. It is
clarified that for the majority of the owners the income from the Airbnb rentals is
supplementary. Another interesting characteristic is that the majority of the sample is working
at the private sector either as an employee (29.1%) or as an owner (25.6%). The majority of
the sample declared that cooperates with Airbnb from 1-2 years. This result highlights the fact
that a large number of rentals have been added recently at Airbnb platform in Greece.
Table 5: “Demographics” of the owners
55 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table 6: Responds from the owners Prior use of the apartment (%) Source of information about
Airbnb alternative (%)
Total days annually of
renting the apartment at
Airbnb platform (%)
Country house 35 Friends / Relatives 50.4 0 – 30 days 8.4
Apartment for
permanent renting
36.4 Social Media 10.5 31 – 60 days 20.3
Rooms to let 4.2 Internet 31.5 61-90 days 23.1
Permanent residence 27.3 Media (TV,
Newspapers etv.)
4.9 91-120 days 16.1
Other 11.9 Other 2.8 121-150 days 9.1
More than 150 days 23.1
Gained income from Airbnb
rentals for you is (%)
Do you agree with the
following sentences5 (mean)
Do you agree with the
following sentences6 (mean)
Basic income 14.9 Airbnb rentals develop
imperfect competition
in the tourism market
2.15 Legal framework is
necessary for the
appropriate
operation of the
market
3.80
Additional income 85.1 Airbnb rentals decrease
the demand of hotels
and relative businesses
of the traditional
tourism market
2.36 Legal framework
may cause
finanacial costs for
the owners
3.2
Airbnb rentals increase
the taxes - leakages for
national economy
2.77 Legal framework
will decrease the
offer of Airbnb
rentals
3.48
5.2 Factor Analysis
Regarding credibility of factor analysis, it has been stated that in order to complete factor
analysis, number of respondents has to be five times larger than the number of the selected
items (Siomkos, 2005, p. 286). In the current study the number of participants was 218 (from
286 due to missing values) and number of selected items 17 so the credibility is well stated.
Table 7 shows the variables that have been tested in the factor analysis and refer to the
perspective of the owners in terms of the expected benefits either for them or for the host
destinations in general. Most of the examined variables presented a mean over 3 with the
highest at 4.44 and the lowest 1.997. It has to be highlighted that only three of them have a
mean below 3. This fact depicts high expectations from the perspective of the owners. It has
to be highlighted that the variables 1 to 5 that have presented the highest means are variables
that depict the fact that the choice of entering in the Airbnb platform actually was an expected
solution in real-life problems – such as decreased family and personal income. In other words,
the decision of renting the apartment was not less affected by factors such as trends or cultural
and social comprehension.
Table 7: Means and Standard Deviation of each variable
Variables of expected results from Airbnb rentals Mean Std. Deviation
1. Additional Personal income 4.44 .926
2. Additional family income 4.36 .987
5 Answers was based on 5-point Likert Scale (5=Totally agree totally 1=Disagree) 6 Answers was based on 5-point Likert Scale (5=Totally agree totally 1=Disagree) 7 Answers was based on 5-point Likert Scale (5=Totally agree totally 1=Disagree)
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 56
3. Exploitation of my own property (as initial motive) 4.07 1.067
4. Exploitation of personal property (in general) 4.06 .894
5. Solution during the financial crisis 4.01 1.160
6. Increasing travel capability (affordable holidays) 3.91 .932
7. Increasing travel capacity (increasing travelling) 3.60 1.078
8. Social and cultural improvement of the rentals' area. 3.57 1.179
9. Distinctive touristic image for some of the areas 3.52 1.053
10. Personal employment 3.51 1.067
11. Creation of new touristic areas inside the cities 3.49 .990
12. Cultural exchange and comprehension 3.35 1.125
13. Increasing repeat visitors 3.29 1.075
14. Social bonds between hosts and visitors 3.18 1.092
15. Employment solution 2.98 1.504
16. Current trend 2.02 1.179
17. Need for socializing 1.99 1.129
Results from analysis (principal components factor analysis with varimax rotation)
revealed 4 factors with an eigenvalue of at least 1.811 and explained 63.172% of Total
variance. Table 8 presents the results of factor analysis: factor loading for each variable item
and the relative eigenvalue. Also, the reliability of each factor is presented from the relative
number of Cronbach Alpha. The results clearly show that examined variables can be
combined to four factors which can be described with the following titles: 1. Benefits for
destinations, 2. Social and cultural benefits, 3. Personal benefits, 4. Additional alternative &
solution.
Table 8: Variables of expected benefits from Airbnb rentals (4 factors)
Variables of expected benefits
from Airbnb rentals
Factor
Loading
Eigenvalu
e
Variance
explained
(%)
Cronbac
h Alpha
F1: Benefits for destinations 4.743 27.900 .884
Increasing travel capacity
(increasing travelling)
.839
Distinctive touristic image for some
of the areas
.838
Creation of new touristic areas
inside the cities
.813
Increasing travel capability
(affordable holidays)
.763
Social and cultural improvement of
the rentals' area.
.734
Increasing repeat visitors .546
F2: Social and cultural benefits 2.242 13.191 .838
Need for socializing .763
Social bonds between hosts and
visitors
.634
Cultural exchange and
comprehension
.603
57 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
F3: Personal benefits 1.943 11.427 .674
Exploitation of my own property
(as initial motive)
.817
Additional Personal income .665
Exploitation of personal property
(in general)
.545
Personal employment .540
F4: Additional alternative &
solution
1.811 10.654 .534
Solution during the financial crisis .856
Employment solution .639
Additional family income .555
Total Variance Explained 63.172%
5.3 Cluster Analysis
Regarding cluster analysis’ results, dendrogram of Hierarchical analysis revealed that two-
clusters solution should be accepted. Nevertheless, k-means cluster analysis for three- and
four- cluster solutions was implemented in order to test other alternatives. Finally, the
solution of two clusters was chosen as the most effective differentiation of the sample. Table
9 presents the respective results of cluster analysis and the mean values of the variables for
each factor of each created cluster. First cluster represents the 39.4% of the sample and
presented a mean score of 2.93 to all the factors. Specifically, 1st cluster’s respondents
declared as important only the variables of 3 and 4 factor which means that focused on
personal benefits and alternative solution of employment and family income. On the other
hand, second cluster represents more than the half of the sample (60,6%) and presented a
mean score of 3.94 to all variables included in the factor analysis. Clearly, the majority of the
sample declared that the expected benefits of Airbnb rentals can affect positively both
individuals and destinations.
Table 9: “Expected benefits” factor means for each cluster
Overall
mean
(n=218)
Cluster 1
(n=86)
Cluster 2
(n=132)
F1: Benefits for destinations 3.55 2.82 4.03
F2: Social and cultural benefits 2.79 2.10 3.24
F3: Personal benefits 4.05 3.62 4.34
F4: Additional alternative & solution 3.78 3.19 4.16
Total to variables included in the factor
analysis8 3.54 2.93 3.94
Note: Answers was based on 5-point Likert Scale (5=Totally agree totally 1=Disagree)
5.4 Characteristics of the revealed clusters
Furthermore, authors implemented additional statistical tests in order to check the correlation
between various answers of the questionnaire and cluster categorization. Specifically, chi-
square tests were implemented and the following variables (derived from the whole
questionnaire) appear to have a strong correlation with the final categorization of the clusters:
8 Removed variable: “Current trend”
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 58
Days of rental (x2=18.964, df=5, p=0,002): It seems that owners that rent their houses for
0-30 days tend to be categorized to the first cluster and vice versa.
Legal framework will decrease the offer of Airbnb rentals (x2=29.465, df=4, p=0,000):
Owners from the 1st cluster expect that the application of the legal framework will decrease
the offer of Airbnb rentals (maybe this is because of the fact that they are more focused on
their personal benefits – so the resistance from this type of owners will be stronger)
Annual personal income (x2=19.995, df=4, p=0,001): Owners from the 1st cluster – in
terms of percentages – tend to declare higher personal annual income.
Airbnb rentals decrease the demand of hotels and relative businesses of the traditional
tourism market. (x2=20.757, df=4, p=0,000): Owners from the 2nd cluster seems to disagree in
higher percentages than the owners from the 1st cluster.
From the above analysis it is clarified that sharing economy has been a benefit for
most of the owners mainly. Airbnb rentals provided with alternative and additional personal
and family income
6. Conclusion
The main conclusions of the survey are the following:
The economic crisis in Greece and the income opportunities are consisted of main reasons
due to which the owners decided or were “actuated” to join the Airbnb platform. Other factors
which affected on the above decision are current trends, cultural and social impacts, etc.
The perceptions of the owners in terms of the expected benefits from the sharing economy
are concluded in four factors: Benefits for destinations, Social and cultural benefits, Personal
benefits and Additional alternative & solution.
The majority of the sample argued that there are various positive socioeconomic impacts
that highlight the importance of sharing economy to local societies, such as increased income,
economic opportunities, enhanced opportunities for travelling (demand side), additional
demand for local businesses etc.
Owners' recognition that the sharing economy, on the one hand, is conducive to
increased travels and expanding tourist demand and on the other hand has multiple benefits
for themselves and for host destinations, leads to an understanding of the rapid spread of the
phenomenon. However, several issues and aspects of the sharing economy remain to be
investigated.
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Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 62
The Challenge of Spatial Information Accessibility for Agricultural
Policies: Case of Pakistan
Abstract Agriculture is directly linked to the socio-economic development of every region. Agriculture
impacts us all, whether we are seeking food security, better health or striving to conserve
natural resources. Goal 2 of Sustainable Development Goals (SDGs) underlines the
significance of agriculture as a means to achieve food security. United Nations in its recently
published report titled “World Economic Situation and Prospects 2020”(UN, 2020) has
declared agriculture as one of the global priorities for achieving high-quality health care and
formal employment opportunities. Agriculture is a spatial subject. Policy makers demand
unrestricted access to spatial data of various kinds in order to address agricultural issues and
for evidence-based policy-making. Therefore, what types of spatial datasets are required for
agricultural policy-making is a relevant question which is the objective of this paper. This
paper also explores agriculture in Pakistan, main challenges faced by the agriculture sector of
the country, and how many as well as what kind of spatial datasets are required to address
these policy challenges.
Keywords: Agriculture, Spatial information, Socio-economic, Challenges, Pakistan
Asmat Ali1 and Muhammad Imran2
1Corresponding-Address: Asmat Ali, PhD Student, Institute of Geoinformation & Earth Observation, PMAS-
ARID Agriculture University, Rawalpindi, Pakistan Email: [email protected] 2Corresponding-Address: Muhammad Imran, Institute of Geoinformation & Earth Observation, PMAS-ARID
Agriculture University, Rawalpindi, Pakistan. Email: [email protected]
63 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Introduction
Agriculture refers to the set of process and activities consisting in cultivating soils, producing
crops and rearing animals; it includes harvesting, milking, breeding animals, and keeping
animals for farming purposes (INSPIRE, 2013). The agricultural system in the world is facing
tremendous pressure due to rising population, urbanization, climate change and environmental
stresses(Ghosh, 2019; Zhai et al., 2020). The Pakistan Vision 2025 (Government of Pakistan,
2014) strategy also notes, “The combination of increasing global population, changing
consumption patterns, stagnant agricultural technology, finite cropland, and growing water
stress in the most populous areas has raised the spectre of famines and persistent food
scarcity” (p.17). The Food and Agriculture Organization (FAO) of the United Nations has
estimated that food production will have to be increased by at least 60 per cent to meet the
needs of the world’s expected population of 9 billion by 2050 (FAO, 2014a). This is a great
challenge for global agriculture as one in eight people currently face food insecurity. This is
the reason, agriculture is a global priority because it has direct relationship to economics as
finds (Gardner, 1978; Y. Liu et al., 2020; Mihai, Florin & Latu, 2020). Kamilaris, Assumpcio,
Blasi, Torrellas, & Prenafeta-Boldú (2018) also argue for the same, “The central role of the
agricultural sector is to provide adequate and good-quality food to an increasing human
population and, because of its importance and relevance, it is on the focus of the global policy
agendas”. United Nations in its various reports and findings has underlined the need to invest
in agriculture sector not only for achieving food security and better health care as well as
economics but also to provide employment opportunities to the quickly growing population of
the world.
2. Agriculture in Pakistan
Pakistan is an agricultural country. It has an area of 796096 km2 and population of 204.65
million(Government of Pakistan, 2020). Agriculture in Pakistan consists of a vast spread of
crops, livestock, fisheries, rangelands, and forestry(I. Khan & Khan, 2018). The country has
four provinces namely Punjab, Sindh, Khyber Pakhtunkhwa (KPK) and Balochistan. Punjab
is the agricultural heartland of Pakistan, accounting for 73% of the total cropped area of the
country whereas Sindh province account for the second largest cropped area (14%) of the
country followed by KPK (7%) and Balochistan (5%)(Zulfiqar & Thapa, 2017). Pakistan is
the sixth most populated country in the world and agriculture is the backbone of its
economy(Ali & Erenstein, 2017; Government of Pakistan, 2016, 2018b, 2015; M, 2016; A.
Ullah et al., 2020). Pakistan has huge potential to enhance economic contribution of
agriculture sector through improved productivity(Government of Pakistan, 2019a). The
growth or decline of the agriculture sector directly affects other sector like service sector as
notes (Government of Pakistan, 2019a), “Services [sector] growth was adversely affected by
the slowdown in agriculture”(p.6). Agriculture in Pakistan is not only a source for providing
food, feed and fiber but also contributes to growth as a source of raw materials for industry,
and therefore also plays a vital role in Pakistan’s exports earnings.
2.1 Sustainable Development Goals
In January 2016, the United Nations General Assembly launched 17 Sustainable Development
Goals (SDGs) which are intended to be achieved by the year 2030. In collection of the 17
SDGs, Goal 1. End poverty in all its forms everywhere, Goal 2. End hunger, achieve food
security and improved nutrition and promote sustainable agriculture, Goal 3. Ensure healthy
lives and promote well-being for all at all ages, Goal 8. Promote sustained, inclusive and
sustainable economic growth, full and productive employment and decent work for all, Goal
10. Reduce inequality within and among countries, Goal 13. Take urgent action to combat
climate change and its impacts and Goal 15. Protect, restore and promote sustainable use of
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 64
terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and
reverse land degradation and halt biodiversity loss are directly or indirectly related to
agriculture.
On 16th February 2016, the Parliament of Pakistan unanimously approved the 17
Sustainable Development Goals (SDGs) as the national development agenda(Government of
Pakistan, 2019a). On one hand, there are many synergies among SDGs, and they are mutually
supportive, such as poverty eradication (Goal 1) and hunger eradication (Goal 2) as points out
the report (United Nations, 2019). “On the other hand, the 2030 Agenda also implies trade-
offs, e.g. between employment generation and rising productivity (both targets of Goal 8) and
between construction of physical infrastructure (Goal 9) and preserving people’s settlements
(Goal 11)” (Basnett & Bhattacharya, 2015). Countries therefore has to prioritize among
SDGs, due to the limited resources and national circumstances (Donoghue & Khan, 2019).
Government of Pakistan has prioritized for achieving SDGs, and has taken certain steps
including data portal development that is being tested before its launch (Government of
Pakistan, 2019a). Agriculture sector can facilitate in achieving objectives of SDGs 1, 2, 5, 6,
8, 13, 16, and 17(Government of Punjab, 2018). The important role of agriculture in
achieving the SDGs is described in Table 1.
Table 1: Role of agriculture in achieving SDGs
Sustainable Development Goal Importance of Agriculture
Goal 1. End poverty in all its forms
everywhere.
Agriculture is important for ensuring food security
and reducing poverty(Ali & Erenstein, 2017).
Agricultural progress is a potent force in reducing
poverty (OECD & Brooks, 2012). Agriculture
remains in general two to three times more effective
at reducing poverty than an equivalent amount of
growth generated in other sectors (Christiaensen et
al., 2011).
Goal 2. End hunger, achieve food
security and improved nutrition and
promote sustainable agriculture.
The central role of the agricultural sector is to
provide adequate and good-quality food to an
increasing human population and, because of its
importance and relevance, it is on the focus of the
global policy agendas(Kamilaris et al., 2018).
Goal 3. Ensure healthy lives and
promote well-being for all at all ages.
Rapid access to [agricultural] data and information
is crucial to the economic, environmental, and social
well-being of our global society(National Research
Council, 1993).
Without agriculture, it is impossible to live a healthy
live as agriculture is the means to provide food for
living a healthy life.
Goal 8. Promote sustained, inclusive
and sustainable economic growth, full
and productive employment and
decent work for all.
With more than two-thirds of the world’s poor living
in rural areas, higher rural incomes are a prerequisite
for sustained poverty reduction and reduced hunger
(OECD & Brooks, 2012).
Goal 10. Reduce inequality within and
among countries.
Agriculture can help to reduce economic inequality
among countries.
Goal 13. Take urgent action to combat
climate change and its impacts.
The effects of climate change can be observed
across regions. In Europe, for example, heat waves
have become more frequent and intense. This has
caused extensive damage in agriculture and forests
to the point that some forest areas are on the brink of
65 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Sustainable Development Goal Importance of Agriculture
collapse (UN, 2020)
Climate affects agriculture. The role of agriculture is
not only crucial in mitigating, but also in adapting to
climate change (FAO, 2019).
Goal 15. Protect, restore and promote
sustainable use of terrestrial
ecosystems, sustainably manage
forests, combat desertification, and
halt and reverse land degradation and
halt biodiversity loss.
Intense heatwaves and dry spells are likely to cause
widespread wildfires and agricultural losses (UN,
2020).
As shown in Table 1, it can be concluded that for achieving all SGDs in general and
specifically the SDGs mentioned above agriculture sector can play a pivotal role as finds
Mihai, Florin & Latu (2020), “To achieve all range of SGDs across the globe, proper attention
must be paid to rural development perspectives such as quality of life improvement,
sustainable agriculture, rural resilience, and circular economy and reduced inequalities”.
3. Role of Agriculture in National Economy
Agriculture is the engine of economic growth, and agricultural growth is the cornerstone of
poverty reduction. Agriculture is one of the pillars of Pakistan’s economy(Government of
Pakistan, 2014). The agriculture sector of Pakistan contributes 18.9 percent to GDP and
absorbs 42.3 percent of labor force(Government of Pakistan, 2018b). Agriculture is also an
important source of foreign exchange earnings and stimulates growth in all sectors as finds
(Government of Pakistan, 2019a), “Therefore, policies aiming to improve agriculture growth,
improve governance in all sectors”(p.8). Agriculture is still a major source of employment and
income for a vast majority of the poor in Pakistan (M. H. Khan & Imam, 1985). Agriculture
problems in Pakistan disturb the economic growth, in 1947, the contribution of
agriculture towards GDP was 53% but it fell by 21% in the last year (Azam & Shafique,
2017). The contribution of agriculture sector in the GDP of Pakistan has decreased and the
sector is facing severe stagnation in productivity and declining growth(Ghazal et al., 2015;
Government of Pakistan, 2014, 2019a; I. Khan & Khan, 2018) as shown in Table 2 and Figure
1.
Table 2: Role of agriculture in national economy (%)
(Source: Pakistan Bureau of Statistics)
Year Share in
GDP
Employment Exports Imports
2014-15 20.9 43.5 16.8 18.7
2015-16 19.8 42.3 16.5 18.7
2016-17 19.5 42.3 15.5 17.7
2017-18 18.9 42.3 17.8 16.0
2018-19 18.5 38.5 17.1 17.5
From Table 2, it is evident that agriculture's share in economy and employment has
declined. Similarly, agriculture's share in exports and imports is not a healthy sign, too. Like
rest of the world countries, there are two basic principles of agriculture in Pakistan, too.
Firstly, to provide suitable quantity of food to the population, secondly provision of
employment to the people connected to agriculture. It is a fact that economic progress and
prosperity of a country like Pakistan depends on its agriculture. Moreover, raising living
standards in poorer states would also require increasing productivity in the agricultural
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 66
sector(OECD, 2017). Due to this reason, policy makers always try to make utmost progress in
these two fields. Although Pakistan is also trying to make progress in the field of agriculture
and industry, however, unfortunately a tangible speed and progress is not visible in the fields
as finds (Malik et al., 2016). Pakistan is considered as the best agricultural country due to its
four seasons, fertile land and canal irrigation system. Due to these features, it is one of the top
list agricultural country in crops, fruits and vegetables. In the past, foreign invasions took
place to fulfil their food necessities. The dilemma is, presently the region is unable to meet the
food demands of millions of its residents (Fatima et al., 2014). In spite of hard work, neither
there is an increase in the production nor a decrease in problems of farmers. Contrary to this,
most of the agricultural countries in the world are using spatial techniques and tools such as
Geographical Information Systems (GIS) and Remote Sensing (RS) to gain maximum
production by investing relatively less efforts and time. Unfortunately, in Pakistan neither
there is a strong agricultural policy nor Government of Pakistan (GOP) can tap the benefits by
using scientific inventions in agriculture like use of GIS and RS. Although, benefiting GIS
and RS for agriculture like many other countries is obviously not new in Pakistan. Most GIS
and RS applications cannot be developed with single dataset. Therefore, multiple spatio-
temporal datasets collected and locked by various organizations are required to be compiled
that are accurate, structured and up to date, as well. This implies that sharing of the spatial
datasets is crucial for developing reliable GIS applications to support policy making process
for efficient decision making in the areas such as exploration and monitoring of natural
resources, climate change as well as managing and mitigating natural disasters that are a
constant threat to agriculture.
Figure 1: Declining contribution of agriculture sector in GDP
(Source: World Bank)
The above scenario demand immediate attention to find out the root causes of
declining agriculture in Pakistan because agriculture’s declining share in GDP and
employment is inevitable as economies develop(Byerlee et al., 2009; Cervantes-Godoy et al.,
2008). Poor agricultural productivity can be related to the low use of improved seed, use of
inappropriate fertilizer, inadequate irrigation, and lack of incentives for farmers in the absence
of remunerative markets as finds Duncombe (2018). The annual plan 2019-20 (Government
of Pakistan, 2019a) also aim at, “There is dire need to enhance agricultural productivity and to
introduce high value crops including horticulture, livestock, poultry and fisheries to enhance
income of the farmer, reduce imports and expand export base of the country” (p.ix). Large
67 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
part of Pakistan is tropical and for such regions long-term growth policies should be
reoriented to favor small farmers instead of big agribusiness players to maintain food security
and social equity (Boron et al., 2016).
Since the emergence of Pakistan, the reigning governments have failed to adopt a viable
mechanism for formulation and implementation of public policies (Sirajul, 2015). The task for
governments is to make sure that the right policies and institutions are in place (OECD,
2010). But in case of Pakistan, politically elected government had always served their own
interests rather than public issues (Sirajul, 2015). Habib (2015) suggested that for the survival,
growth and stability of agricultural sector it is compulsory for every government to make an
effective policy.
4. key Issues to Agriculture in Pakistan
4.1 Review of Existing Policy Documents
In order to identify issues to agriculture in Pakistan, first of all, existing policy documents are
critically reviewed and analyzed as the policy documents are authoritative, and original
information source, as well as governing tools (Macheridis, 2015). The review of existing
policy documents also facilitates to understand the institutional settings and the overall policy
context in a certain domain and their inter-linkage in a region. This study critically reviewed
twelve relevant policy documents. The scope of these policy documents ranges from
agriculture, economic development, digitization of sectorial information to climate change.
The detail of policy documents reviewed is listed in Table 3.
Table 3: Policy documents reviewed for identification of issues to agriculture
Annual Plan 2019-20
National Food Security Policy (2018)
National Water Policy (2018)
Pakistan Statistical Year Book (2018)
Pakistan Economic Survey (2018-19)
Digital Pakistan Policy (2018)
Pakistan Vision 2025 (2014)
National Climate Change Policy (2012)
National Environment Policy (2005)
Agriculture Policy Khyber Pakhtunkhwa: A Ten-Year Perspective
(2015-2025)
Agriculture Policy of Sindh (2018)
Punjab Agriculture Policy (2018)
Annual Plan 2019-20 (Government of Pakistan, 2019a) identify climate change, shortage of
irrigation water, use of low quality inputs such as inferior seed and fertilizers, and reduction in
sown area as the main issues faced by the agriculture sector of Pakistan.
National food security policy 2018 (Government of Pakistan, 2018c) highlight key issues
faced by agriculture sector of Pakistan. The major issues mentioned in the policy document
include, problems with the quality, quantity, and timing of supply of agricultural inputs,
inefficient utilization of land and water resources, lack of infrastructure and technologies,
trade restrictions, climate change effects on agriculture and livestock. And un-capitalized
potential of mountain agro-ecological zones, degradation of natural resources, low priority to
mainstreaming women contribution and slow rate of diffusion of technological innovations.
National water policy 2018(Government of Pakistan, 2018d) mention major challenges
faced by the water sector of Pakistan such as climate change, trans-boundary water issues,
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 68
siltation of existing dams, replacement of water storage bodies and lack of equity in water
allocation at a regional levels. The issues including scarcely of fresh water resources and lack
of awareness about the impending threat of water scarcity, salt imbalances in irrigated lands
and the decreasing soil quality resulting in reduced yields are also stated in the policy
document.
Pakistan statistical year book (2018) was reviewed. From the statistical data given in the
book, it reveals that labour force working in the agriculture sector is gradually decreasing
whereas temperature of the region is increasing due to climate change. The share of
agriculture in GDP is also on the decline.
Pakistan economic survey 2018-19(Government of Pakistan, 2019b) attribute the under-
performance of agriculture sector due to reduction in the area of cultivation, lowe water
availability and drop in fertilizer off take as well as climate change. The issue of food security
is also underpinned in the document.
The digital Pakistan policy(Government of Pakistan, 2018a) highlight issues including lack
of agriculture information portal and integration of national as well as provincial databases in
addition to duplication of efforts in data collection. The policy underscores the need to
“revamp Geographical Information Systems (GIS) for Pakistan to monitor the environment
and plan sustainable agriculture” (p.14). The policy underpins the preparation of agriculture
related information in GIS format such as digital mapping, land use, soil types, meteorology,
ecology, oceanography, hydrology and agricultural records in order to integrate national and
provincial databases to avert duplication and ensure synergy (p.17).
Pakistan vision 2025(Government of Pakistan, 2014) identify, slow rate of technological
innovation, limited adoption of progressive farming techniques, problems with input supply,
limited investment in construction and maintenance of infrastructure. The policy also
mentions trade restrictions, pest and livestock disease problems, limited amounts of credit for
agricultural production and the lack of agriculture-specific financing as the major factors
underlying the poor performance of the agriculture sector.
National climate change policy(Government of Pakistan, 2012) mention issues including,
increased health risks, stress on water resources, migration of agriculture related population,
siltation of major dams and threat to coastal areas due to projected sea level rise.
National environment policy(Government of Pakistan, 2005) highlight issues which have
direct relevance for agriculture including pollution of fresh water bodies and coastal areas, air
pollution, soil degradation, lack of water management, deforestation, natural disasters and
climate change.
Agriculture policy of KPK(Government of Khyber Pakhtunkhwa, 2017), identify issues to
agriculture in the province including climate change and natural hazards, lack of
transportation infrastructure , food insecurity, increasing cost of agricultural inputs and quality
concerns, shrinking financial resources, low productivity and profitability, declining water
supply and land degradation, poorly managed natural resources and gender biases in
agriculture. The policy also underscores post-harvest losses, inadequate agriculture research
and development (R&D) system.
Punjab agriculture policy 2018(Government of Punjab, 2018), highlight challenges faced
the agriculture in the province including, lack of coherent policies, out dated agriculture
produce marketing system and outdated institutional structure, climate change and poor profit
for farmers. Lack of investment in human capital and diversification, depleted natural
resources and low growth as well as productivity are mentioned as issues to the agriculture,
too.
Agriculture policy of Sindh 2018 (Government of Sindh, 2018) mention major issues to the
agriculture in the province including problems with agricultural inputs (seed, site specific
fertilizer), poor infrastructure (Transport and storage), lack of institutional credit, poverty,
gender biases and climate change. The issues also include malnutrition, lessening agricultural
69 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
labor force, low yield, water availability, traditional cultivation methods, lack of food
processing technology and limited quality control facilities.
4.2 Review of Scientific Literature
Zulfiqar & Thapa (2017) in their study identified environmental, economic and social issues
that hamper agricultural sustainability at provincial level in Pakistan. They used secondary
data, covering the period of 2005/06–2012/13 for their study. Crop diversification, soil
salinity, and the use of organic and inorganic fertilizers and pesticides were the indicators
considered by them for environmental sustainability analysis. For economic sustainability
analysis, they used, change in overall crop production and stability of crop production as
indicators. Whereas employment of rural labor force and food security were used as indicators
for social sustainability analysis. They find, “there are regional differences in agricultural
sustainability in Pakistan”. For example, they noted that inorganic fertilizer, pesticides and
groundwater for irrigation are being over utilized in Sindh and Punjab. On the other hand,
limited use of fertilizer and pesticides in some areas and altogether no use in other areas of
KPK and Balochistan is impeding sustainable agricultural production. Moreover, they find
that in the coastal areas of Balochistan, groundwater for irrigation is further reinforcing
agricultural unsustainability. They recommended “to formulate effective regional agricultural
policies based on local level research and revise agricultural extension structure in order to
incorporate need-based services with better dissemination of information and farm level
trainings”.
I. A. Khan & Khan (2018) through SWOT (Strength, Weakness, Opportunity and
Threat) analysis, identified issues faced by the agriculture sector of Pakistan. The main issues
identified by the authors include, land and water productivity/sustainability, climate change,
stagnant yields, diversification, postharvest losses and markets, social disparity and gender,
malnutrition and food security (p.5).
Land and water productivity/sustainability
Peerzado, Magsi, & Sheikh, (2019) carried out study to explore the nexuses between
urbanization and agricultural land conversion in Hyderabad, Pakistan. They find that “70
percent of agricultural land has been sold and converted in urbanization in Hyderabad district”
and only 16 percent of the population is engaged in agricultural farming. According to them,
reasons for selling agricultural land are, “due to certain economic, social, financial and
agricultural related reasons”. They highlight that this scenario can cause shortage of food in
addition to issues like social, cultural, environmental and economic instability not only in the
study area but also in the country.
R. Ullah, Shivakoti, Kamran, & Zulfiqar (2019) conducted a reach study in province
of Khyber Pakhtunkhwa, Pakistan. They identified that land ownership status plays important
role in adaptation and mitigation of climate change threats. Farmers who own no land are the
least interested in adaptation and mitigation of climate change threats. On the other hand,
farmers who own land try to adopt the latest technological means to combat climatic threats.
Saltwater intrusion is also one of the problems being faced in coastal areas of Pakistan. The
Indus Delta, located near Karachi is an example of seawater intrusion and land degradation
due to climatic and environmental conditions(Rasul et al., 2012). Salinisation and
waterlogging in the provinces of Punjab and Sindh is due to over-irrigation (Chandio et al.,
2011).
I. A. Khan & Khan (2018) argue that “subsistence-oriented farming practices, uneven
distribution of ownership rights, and fragmentation” (p.6) hamper optimal utilization of land
and water resource. Moreover, they find that the ground water level is declining.
Accordingly, they suggest “to build new water reservoirs and the silting up of existing
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 70
storage” (p.7). Moreover, they find that subsoil water being used for agriculture is negatively
affecting soil health and organic matter content, and therefore sustainability of the entire
agricultural system of the country. Aslam and Prathapar (2006) also found that major river
basins such as Indus Basin in Pakistan is undergoing salinisation. In Pakistan, about 6.2 Mha
of agricultural land is affected by salinity(NIAB, 1997).
Figure 2: Important issues to agriculture policy in Pakistan
Source:(I. Khan & Khan, 2018)
Akhter & Erenstein (2017) conducted study for assessing farmer use of climate change
adaptation practices and impacts on food security and poverty in Pakistan. They find that, the
majority of farms in Pakistan are small-scale with 90% of the farms being two hectares or less
and “one-third of the farmers are pure tenant farmers having no land ownership”. They argue
that the farmer with no land ownership or having small size farms can not adapt to climate
changes. However, “Farmers with large landholdings are likely to have more capacity to try
out and invest in climate risk coping strategies”.
It is argued that despite the fact, Pakistan owns one the best canal system in Pakistan,
the sources of irrigation are scarce in the country as water is wasted in distributaries and fields
due to lack of integrated water management strategy as well as system. This can also be
attributed to illiteracy among farmers as most of them cannot learn new methods for irrigation
such as drip irrigation. The dilemma is, large quantity of rain, fresh and river water is lost in
oceans and there are no adequate measures to store this water. On the other hand, excessive
load-shedding affects tube wells, and this is another setback for watering the crops. There is
no specified land use system in the country and not a secure source of water, therefore
farming results in low productivity (A. Ullah et al., 2020).
There is a close relationship between water resources and climate change, “Water
resources are inextricably linked with climate; this is why the projected climate change has
such serious implications for Pakistan’s water resources”(Government of Pakistan, 2012).
71 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Climate change
Agriculture in Pakistan has been negatively affected by climate change(Shukla et al., 2019,
p.452). Abbas et al. (2017) finds that from 1980 to 2014, there is an average shift of 4.6 days
per decade earlier in the case of spring maize growing periods whereas sowing of autumn
maize has been delayed 3.0 days per decade. Similarly, Tariq et al. (2018) found that due to
rise in temperature from 1980 to 2016, there are shifts in sowing, emergence, anthesis, and
maturity for fall and spring crops. Extreme weather condition and natural disasters negatively
impact agricultural yield, food production and food security(Dizon et al., 2019).
Climate change worsens the adverse effects of weather on agriculture. Climate change
has been noted as a new threat to agriculture and food security (Ahmad, Farooq, & Umar,
2016; Gahukar, 2011). In Pakistan, India, Nepal, and China, farmers have noticed an increase
in floods, landslides, drought, and disease, due to climate change(Dizon et al., 2019). These
events can be attributed to a decline in the production of main crops and an increase in food
insecurity (Hussain, Rasul, Mahapatra, & Tuladhar, 2016). In Pakistan most of farmers are
poor and less educated therefore they are not able to employ climate change adaptation
strategies for improving agricultural yield and ultimately food security(Ahmad, Mustafa, &
Iqbal, 2016; Akhter Ali & Erenstein, 2017). The rainfall has two-fold effects i.e. less than
average rainfall or more than average both has negative effects on agricultural productivity.
For example, in Pakistan, more than average rainfall is the source of floods that cause huge
losses in agriculture (de Vries & Asmat, 2016; Dorosh et al., 2010). Therefore, the food prices
were high causing more food insecurity in Pakistan (Shukla et al., 2019,p.516).
R. Ullah, Shivakoti, Kamran, & Zulfiqar (2019) find that agriculture in the region is
facing several threat due to climate change and the threats are beyond the control of the local
farmers. They highlighted the “significant role of land ownership status, along with
perceptions of risk sources and attitude towards risk, on farmers’ decisions of adopting off-
farm diversification and credit reserves” to cope with climate change issues.
Srivastava (2019), provided evidence of the adverse climate change effects on
agriculture, livestock production, PHM of fresh produce, food quality, and food security.
I. A. Khan & Khan (2018) find that Pakistan is highly vulnerable to climate change
affects. Accordingly, they call for disaster preparedness in order to stop potential loss of crops
and livestock. The authors assert that due to improved “access to software and data gathering
devices (GIS)”, government should focus on developing decision support systems as it would
be useful in sustainable agriculture policy formulation.
Stagnant yields
LeGouis, Oury, & Charmet (2020) conducted study to investigate the causes of stagnation in
productivity of wheat as is the case with Pakistan, too. They identified three groups of factors
are; a decrease in genetic progress, resistance to change agricultural practices and unfavorable
climatic conditions. They conclude that climate change is one of the main reasons causing
stagnation in agricultural productivity. Liu et al. (2016) and Wiesmeier, Hübner, & Kögel-
Knabner (2015) also find that stagnation in productivity is largely due to climate change
impacts.
I. A. Khan & Khan (2018) highlight that “agriculture sector of Pakistan is facing
severe stagnation in productivity and declining growth” (p.9). They attribute the declining
growth of agriculture sector of the country to lack of interest of the farmers in their native
profession, and yield gap in all the major crops such as wheat, rice, maize, cotton, and
sugarcane. They compare yield with other countries of the region and world and find huge
yield gaps. They find that “major reasons for this difference are unavailability of quality seed,
inappropriate sowing (methods and time), weeds, lack of balanced fertilizers, partial
mechanization, and excessive use of unfit irrigation water” (p.10).
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 72
Diversification
Prăvălie (2016) finds that desertification is affecting 38 of 48 countries in Asia and it is a
serious problem in Pakistan (Irshad et al., 2007; Lal, 2018). According to Ponce (2020),
farmers concerns over low or no support from governments for adaptation to climate changes
hamper diversification in agricultural systems which is not good for the sustainability of the
system as a whole. Therefore, climate change can be considered as one of the main reasons
that impede diversification in crops although “Crop diversification, as an agricultural practice,
could lead to climate adaptation and mitigation” (Piedra-Bonilla et al., 2020).
R. Ullah, Shivakoti, Kamran, & Zulfiqar (2019) in their study found that ownership
status of agricultural land help to adopt crop diversification as the farmers not having their
own agricultural land are forced to follow the instruction of their landlords.
Agriculture in Pakistan is dominated by five crops; wheat, cotton, rice, maize, and
sugarcane (I. Khan & Khan, 2018). They argue that the reasons for this include political
economy and the interest of the farmers on food security rather than profitability. They call
for giving incentives to the minor crop growers as it would help to achieve diversification.
Postharvest losses (PHL) and markets
According to Srivastava (2019), postharvest losses (PHL) can be attributed to climate change,
“Climate change has a strong impact on the food industry as it affects cultivation, postharvest
management (PHM), food loss, food quality, and food security”. The effects the changing
climate will have on post-harvest agriculture are well established and this calls for investment
in PHL mitigation(Chegere, 2019).
I. A. Khan & Khan (2018) find that due to lack of storage capacity and access to
agricultural markets that includes “poor transportation, inadequate grading, very heavy spread
in price between consumer and farmer, and tough competition with imported goods” (p.16)
contribute to postharvest losses.
It is argued that small land holder farmers usually do not have transportation means to
take their agricultural outputs to the markets and a middle man appears in most of the cases
who buy their products at low price and then sell it at higher price by transporting the
agricultural products to the big markets.
Social disparity and gender
The participation of women in agricultural activities can help to overcome gender barriers,
enhance gender equality and food security(Shukla et al., 2019, p.70).
However, I. A. Khan & Khan (2018) cite various statistics, to conclude that there is
wide social and gender disparity in Pakistan. According to them, this impedes sustainable
agriculture in the country. The existence of poor physical infrastructures including education,
health facilities, safe drinking water, and sanitation in rural areas cause social disparity in the
country. They argue that although rural women take part in agriculture, but “women are far
less likely to own income-generating assets such as land and livestock or to have a say in
household economic decisions” (p.17).
National food security policy(Government of Pakistan, 2018c) support above findings
and categorically states, “ Low priority to mainstreaming women contribution in value added
agriculture and family nutrition”. Therefore, it is evident that women are given a secondary
role in decision-making in the country.
Malnutrition and food security
Agriculture is two to three times more effective at reducing poverty than other sectors
(Christiaensen et al., 2011) because agriculture tends to employ more poor
people(Christiaensen & Martin, 2018; Ligon & Sadoulet, 2018). Enhancing agricultural
productivity can also improve food security(Dizon et al., 2019). However, the link between
agricultural growth and food security is less clear (Kirk et al., 2018).
Research in India (for example Headey, Chiu, & Kadiyala, 2012; Kolady, Srivastava,
& Singh, 2016; Vepa, Umashankar, Bhavani, & Parasar, 2014) shows that states with higher
73 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
growth in agricultural output have less food insecurity especially among children and women.
Similarly, in Bangladesh, rapid growth in rice yields improved food security situation
(Headey & Hoddinott, 2016; Yu, 2012). Higher growth in agriculture can be achieved by
making use of more inputs (fertilizer, seed, and the like), bringing more land under
cultivation, and enhancing the productivity of inputs and agricultural land(Dizon et al., 2019).
I. A. Khan & Khan (2018) argue that “micronutrient deficiency, known as hidden
hunger, is widespread in Pakistan and well characterized among rural areas” (p.18). The issue
of malnutrition and food security is relatively higher in rural areas as compared to urban
centers, they conclude.
There is a direct relationship of climate change and food security as finds (Ali &
Erenstein, 2017),”…. increasing weather variability and climate change have threatened the
agricultural sector and thereby, have become major barriers to achieving food security and
alleviating poverty in Pakistan”. The climate change “threats lead to major survival concerns
for Pakistan, particularly in relation to the country’s water security, food security and energy
security”(Government of Pakistan, 2018c).
Summary of the main issues to agriculture in Pakistan
From the review of existing policy documents and literature cited above, it reveals that main
issues faced by agriculture sector of Pakistan include, climate change, low availability of
water, low profitability and productivity, deprived physical infrastructure, food insecurity,
quality issues, degradation of natural resources (land, water), outdated cultivation methods,
issues with supply of agricultural inputs and lack of adoption of the latest technology. The
most of the issues faced by the agriculture sector of Pakistan are directly or indirectly related
to climate change.
5. The Role of RS/GIS in Agriculture
Due to large variations in climatic conditions, crops have to suffer from different types of
stresses leading to reduced crop productivity and year to year variability. The conventional
methods of acquiring weather and crop growth status information are reliable, but they are
labour intensive and time consuming. However, recently remote sensing (RS) and
geographical information system (GIS) technologies are gaining importance for acquiring
spatio-temporal meteorological and crop status information for complementing the traditional
methods. Under such conditions, rapidly emerging remote sensing and geospatial technology
can be of great help for crop growth monitoring, identification and management of different
types of stresses and regional yield estimations to sustain the natural resources and
agricultural productivity. Remote sensing data can greatly contribute to the monitoring by
providing timely, synoptic, cost-efficient and repetitive information about the earth’s surface
(Justice et al., 2002). Atzberger (2013) has illustrated five major applications of remote
sensing in agriculture including biomass and yield estimation, vegetation vigor and drought
stress monitoring, assessment of crop phonological development, crop acreage estimation and
cropland mapping, mapping of disturbances and land use land cover changes in addition to
precision agriculture and irrigation management. There was a need to develop fast track and
reliable procedures to make crop forecasts and estimations early in the season or end of
season. Pakistan Space and Upper Atmosphere Research Commission (SUPARCO), the
Space Agency of Pakistan started developing crop area estimation procedures and crop yield
models, based on the application of satellite remote sensing, GIS technology, agronomy, agro-
meteorology, statistics and other allied disciplines.
Korduan, Bill, and Bölling (2004) find that in agriculture, the importance of geo-
information is rising up. Agriculture is dealing with the integration of agricultural applications
to the natural heterogeneity outside in the fields. They argue that using geospatial
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 74
technologies would help in increasing yield and decreasing the means of production while the
environment remains conserved. To assemble necessary information regarding spatial
variability requires spatial data about the soil, the crop, the terrain, the land machinery, and
the applications. For analysis, GIS should be used and that would require collection, and
management of several datasets and therefore much of the time is spent in data management.
Due to availability of various data capturing devices, which support different data formats,
and improperly spatial reference systems one has to transform the data between proprietary
GIS and coordinate systems.
Imran (2013) carried out four studies to develop services for accessing, integrating,
and assessing data and models in the agriculture domain. He finds data integration
problematic due to three reasons i.e. technical, conceptual and institutional. The technical
reasons include various data formats and varying spatial scales. Conceptual barriers include
different interpretations of the data due to lack of common standards and semantics. Whereas
institutional issues such as ownership and copyrights impede data sharing. Accordingly, he
recommends the use of an SDI framework for integrating and upscaling of spatial datasets in
order to develop agricultural services.
Ghazal, Kazmi, & Zubair (2015) conducted study in Pakistan for monitoring and
mapping spatio-temporal dynamics of vegetation cover using Remote Sensing and GIS. They
concluded, that, geospatial technologies are “ideal for mapping the extent of agricultural and
other green bodies”. Bordogna et al. (2016) explored integration of multisource
heterogeneous geospatial data and time series in a case study for agriculture using OGC
standard interoperable SDI architecture and a geospatial data and metadata workflow. They
argue that geospatial information is becoming quite important not only for environmental
researchers, geographers, and social scientists but also among public authorities and citizens
for various purposes such as agriculture. They find that four factors play key role in favoring
SDI development; legislation and new strategies, standardization activities, increasing trend
of available free and open software and decreasing trend of market prices for hardware
resources.
Tóth & Kučas, (2016) find that geospatial information plays a key role in the
implementation of Common Agricultural Policy (CAP) in Europe. However, agricultural
decision makers have to work in order to optimize data integration for achieving transparency.
They underscore the need to establish a framework for information exchange between the
stakeholders. Relating information to location plays a fundamental role in agriculture. The
national spatial data infrastructures (SDI) may provide valuable input for the CAP as the
collected data can be shared within SDI. SDI will also contribute to the maintenance of the
digital topographic databases. They highlight that data sharing will save public resources.
They emphasize on standardization of geographic information in the agricultural domain.
Abdelrahman, Natarajan, and Hegde (2016) integrated RS and GIS for identification
of suitable land for agriculture in Chamrajnagar, India. They identify that remote sensing (RS)
data is useful for estimating biophysical parameters and indices besides cropping systems
analysis, and land-use and land-cover estimations during different seasons and however, “RS
data alone cannot suggest crop suitability for an area unless the data are integrated with the
site-specific soil and climate data”.
Sharma, Kamble, & Gunasekaran (2018) conducted a systematic literature review
(SLR) and selected 120 research articles published during 2000–2018 available in the ISI
Web of Science (WoS) database on applications of GIS in agriculture. They look at GIS as a
computer-based tool analytical tool which exploit spatial data. Accordingly, they mention
following as GIS components, “
Storage of spatial data in digital form.
Management and integration of spatial data collected from different
sources into the GIS system.
75 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Retrieval and conversion of the spatial data in the required formats.
Performing data analytics to convert data into useful information.
Developing different models based on the information.
Display of information model and decision making”.
They find, “GIS is transforming the agriculture sector in incredible ways. The
hyperspectral and multispectral images obtained through the geospatial data is found to be
very useful for analyzing parameters such as crop health and soil moisture”. They concluded
with a call for establishing a framework for GIS data sharing, “There is a need for developing
novel frameworks incorporating different layers or platforms for efficient collection of data,
storage of data, data analysis and information sharing”. They further discussed the need for
data integration, “GIS data can be of high value to the practitioners if it is further integrated
with the data collected from the other sources for deriving meaningful insights”. They found
that GIS data can be helpful for improved decision and policy making in agriculture such as
land suitability analysis, site search selection, impact assessment, resource allocation, and
developing knowledge-based systems.
Honda et al. (2014) provide evidence that farming based on detailed geospatial
information increase yield and reduce the cost of fertilizers and other input resources. They
implemented an agricultural information service platform and tested it on geospatial data
infrastructure for crop modeling. They conclude that usage of web services from geospatial
infrastructure has advantage for the agricultural information service system.
(Kliment et al., 2015) implemented a simple SDI to automate the workflows for
publishing huge amount of metadata, geospatial data and remote sensing images on the Web
in an interoperable and distributed way. They carried out it in a real case study to support the
national agricultural sector of Italy. They found it quite handy for sharing geospatial
information resources with the stakeholders.
Edeme, Nkalu, Idenyi, & Arazu (2020) examined the positive affect of infrastructural
development on agricultural output utilizing panel autoregressive distributed lag (PARDL)
methodology. Physical as well as non-physical infrastructures such as ICT positively impact
positively agricultural productivity, they conclude.
Policies for agriculture consist of government decisions that influence the level and
stability of input and output prices, public investments affecting agricultural production, costs
and revenues and allocation of resources. These policies affect agriculture either directly or
indirectly. Improved agricultural production has been seen as one of the overall objectives for
poverty reduction in the country. The objectives of agricultural sector strategy have been
increasing agricultural growth, seen as important for increasing rural incomes and ensuring
equitable distribution. Due to limited availability of high potential land, it has been envisaged
that increasing agricultural production will have to come from intensification of production
through increased use of improved inputs, diversification especially from low to high value
crops, commercialization of smallholder agriculture, and increased value addition through
stronger linkages with other sectors.
The development of the agriculture sector is therefore important for the development
of the economy as a whole. In the following sections, we review some of the key policy issues
and concerns with respect to the sector’s development.
6. National Food Security Policy
The national food security policy(Government of Pakistan, 2018c) aim to:
Create a modern, efficient and diversified agricultural sector that can ensure a stable and
adequate supply of basic food for the country’s population, and provide high quality products
to its industries for export. It ensures attractive incomes and decent employment for those who
live and work in rural areas; use the resource base in an efficient and sustainable manner;
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 76
flexibly adapt to climate change and be resilient enough to quickly recover from shocks and
emergencies; and ensure that all sections of the population have stable access to adequate,
nutritious and safe foods necessary for a healthy life.
Within this context, the primary function of Government of Pakistan is to act as a
regulator and facilitator, creating an enabling environment that allows the dynamic subsectors,
such as production of high value livestock and horticulture products for both domestic and
export markets, to grow rapidly. A conducive investment environment also needs to be
created in rural areas for processing, storage and value-chain development to provide
employment opportunities, beyond those that can be offered by agriculture itself. At the same
time more proactive policies are needed to ensure inclusive growth that will draw in
vulnerable group such as small farmers, share croppers and non-agriculture workers; address
resource scarcity and degradation issues particularly related to land and water; and bring
about a rapid reduction in hunger and malnutrition. In line with the above, the key elements
of a new agriculture policy for Pakistan will be more innovation and technology based
agriculture that makes efficient and sustainable use of natural resources; redirect public sector
agriculture expenditure by focusing agriculture subsidies to socio-economic groups that need
it most such as small farmers, landless, women, and nomads and transhumant, and public
investments in creation of knowledge, technology and essential infrastructure that would
facilitate and encourage private investments by raising profitability of agriculture and rural-
based activities; and ensure that food is accessible to all sections of the population, in
particular vulnerable groups such as children and women, and is prepared, stored and
consumed in a way that ensures nutritional security.
To better understand the root causes of declining agriculture and failure of agricultural
policies in Pakistan, it is useful to explore that how agricultural policies are made in Pakistan.
7. Agricultural Policy Making Process in Pakistan
Agriculture is the most important sector of the country’s economy (Ahmad & Farooq, 2010;
Akram, Alam, & Iqbal, 2018; Awan & Yaseen, 2017; M. H. Khan & Imam, 1985; Malik et
al., 2016; Government of Pakistan, 2017). The agriculture sector of Pakistan is a provincial
subject. However, the sector is assisted by various federal and provincial government
departments. Federal institutions are mainly responsible for formulating and coordinating
national policies and strategies, such as the import and export of agricultural inputs and
commodities, setting prices of inputs and outputs, enforcing phytosanitary and quarantine
regulations, approval of varieties and seed certification, standardization, compliance of grades
and standards, providing support to national research institutions, and managing marine
fisheries resources (Greer & Jagirdar, 2006). There is a mess of institutions involved in
agriculture policymaking in the country as mentioned in a report published by Asian
Development Bank in 2006. According to the report, there is often excessive government
intervention and too many regulatory departments which are the major impediments in the
promotion of the sector. Policy decisions are mostly based on crisis management and the need
to provide a quick fix to a problem, the report concludes. Ahmad and Farooq (2010) while
discussing major flaws in the existing wheat policies find that considerable inefficiencies in
managing wheat surpluses as the quantities procured were beyond the storage capacities
available with the government departments—hiring private storage facilities at a huge cost to
the nation. It means that the government do not have data of storage capacities or even it has
the data but not making use of relevant data for managing wheat surpluses. Similarly,
Spielman et. al (2016) finds that there is decline in evidence-based policy making related to
agricultural sector issues in Pakistan. According to him, “as a result, growth in the rural
economy has lost momentum, leaving Pakistan's rural population to face continuing high
levels of poverty, and food insecurity, as well as limited access to the public services and
markets required for a modern economy”.
77 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Commenting on the policy making process in Pakistan, Saeed (2013) finds that, “As
far as the development of policies is concerned, Pakistan has a unique process of developing
public policies”. Because, “Pakistan inherited a very strong bureaucratic structure which was
developed to cater the needs of the colonial powers” (Wilder, 2009). Therefore, “The policy
making was basically the domain of the colonial rulers and then bureaucracy was trained to
perform this task at local level” (Saeed, 2013). Whereas according to Sial (2011), “State has
lost its capacity to frame its policies according to its national priorities. Its parliament seems
to have imperfect control over decision-making process. Parliament doesn‘t seem to have self-
regulating capacity” (p. 127). Islam (2001) notes that “the legislatures have traditionally
played minimal role in the country's governance”. Saeed (2013) concludes in a policy making
case study in Pakistan that, “Pakistan ever since its independence has been under the influence
of super powers and donor agencies and most of the policies adopted and implemented in the
Pakistan has been suggested or enforced by them and the role of legislature in this regard has
not been significant at all”. Commenting on the policy formulation process in Pakistan,
Husain (2013) notes that, “Policymaking in Pakistan deviates from the ideal process”.
Meaning that the process is not in accordance with policy literature. According to him, there
are six deviations. First, “The stakeholder consultation is either superficial or the views of the
stakeholders, if found at variance with those of the formulators, do not find any place in the
revised documents”. Similarly, “Ministers feel personally offended if their policy documents
are criticized by other ministers”. “Some slick players with the gift of the gab can make
impressive PowerPoint presentations and mesmerise the audience. They create the impression
that things are going well while the facts are to the contrary”. Therefore, “underlying
problems remain unaddressed”.
Fifth, the capacity of the ministries and provincial departments in preparing policy
papers is limited. They do not have the necessary expertise or competence in the subject to
come up with evidence-based options. The use of systematic data is normally shunned. And
finally, the communication strategy of explaining the rationale and disseminating the policy
widely is almost non-existent in most cases. As the success of the policy depends upon people
outside the government their understanding and support are absolutely crucial.
Investigating public policy making in Pakistan, Hussain (2008) finds that policy
making has been captured by feudal elites and other powerful interest groups. According to
him, “…policy makers work under pressures of deadlines” Therefore, [data] are of no use to
them if they are made available after the deadlines. He is of the view that the policy
recommendations are not implement-able as the researcher; do not take cognizance of the
constraints faced by the policy makers. He asserts that public policy can be informed and
made effective if these are based on primary data collection, surveys. Structured interviews,
field visits and observations. Commenting on the need of multidisciplinary approach, he
argues that, “Most public policy Issues in Pakistan can be resolved only if we dissect them
under a multidisciplinary microscope rather than a single lens prism or a par1icular
discipline’. It means we must have data of various disciplines to inform policy making.
Having multiple datasets would help to stop ‘policy makers from indulging in irresponsible
policies, low return pet projects and rent seeking by their political cronies” (Husain, 2001).
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 78
Figure 3: Policy-making process in Pakistan
“The financial, technical and human resources play critical role in formulation and
implementation of public policy. In case of Pakistan, the country has always has been in short
of financial resources to implement the public welfare projects and there is no proper
utilization of resources in any sphere of development or policy making process. Due to the
corruption and inefficiency of government functionaries, the available resources are always
mismanaged and underutilized. The injustice taxation policy is the main reason of shortages
of financial resources in the country. Since the inception of Pakistan, government has failed to
implement a viable taxation policy where every citizen irrespective of their positions and
political influences should pay the required taxes and evaders liable to be punished according
79 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
to the law. Due to this reason, the budget formulation history of the country has depicted that
most of the presented budgets had been in deficit. It is prudent that there must be sufficient
resources for the successful formulation and implementation of public policies to obtain the
desired objectives” (Sirajul, 2015). Jabeen, Jadoon, & Salman (2016) analyzed public policy
making process and strategies in the specific context of Pakistan. Their findings are that,
“existing process and strategies of policy making are quite generic, linear and mainstream
which provide an overly simplistic and general understanding of the approach in which public
policies are formulated”. Political interests play an important role in policy making of the
country.
Khalid, Mushtaq, & Naveed (2016) argue that public policy means the actions
of the government in order to solve the problems being faced by the nation. They find that
there are three elements of a public policy i.e. what is the problem, its players and their
policies. They identify factors which cause failures of public policies in Pakistan. According
to them, the factors include, lack of relevant information, lack of coordination among
government institutions, irrelevant education of the politicians, lack of financial resources,
corruption and untrained civil servants in the specific discipline, political instability and lack
of research.
From above discussion, it can be concluded that policy making capabilities of the
government institutions in the country can be seen as poor. The reasons can include; lack of
coordination, lack of usage of scientific data and research, underperforming institutions,
exclusion of some relevant stakeholders and relying on inaccurate and incomplete data. There
is a need to change the current policy making process as governments in Pakistan secure their
own interests, and the vast majority of people including farmers are far from the basic
necessities and facilities(M. Abbas et al., 2016). Therefore, data should be used for evidence
based policy making instead of telling tales as “to assess the growth in global demand for
agricultural output, one needs estimates from many sources (Norton, 2016). The study suggest
“to enhance the development policymaking capacity of the institutions, by arranging capacity-
building and training programmes for the policymakers” (United Nations, 2019) in the areas
of agricultural development planning and financial analysis etc.
8. Specifics of Agricultural Information and Policies
Agriculture is spatial in nature. All agricultural activities take place at some geographic place.
Similarly, “all agricultural information is located in a certain geographic space, and possesses
spatial variation. Therefore, all agricultural information may be called agricultural geographic
information”(Y. Q. Huang et al., 2012). It is argued that almost all the problems faced by
agriculture are spatial. Agricultural policies are crafted for addressing these spatial problems
and obviously spatial decisions are made. The final decision is based on two main questions:
1) what should be done? (Action) and 2) where it should be implemented (Location)?
(Chakhar & Mousseau, 2008; Malczewski, 1999; Malczewski & Rinner, 2015). The first
question refers to the policy or decision-making process, and the second concerns the
‘receptor’ of the final decision, namely, the most suitable location for the development of a
specific agricultural activity. Most application that are built in agriculture exploit spatial
information. Farmers consider themselves as ‘information poor’, and news about new
agricultural technologies that improve productivity is not reaching them(Government of
Pakistan, 2014). Agricultural information consists of four interrelated components, namely
spatial position, spatial relationship, attribute, and temporal property(Fonseca et al., 2003).
Agricultural information “products (such as irrigation data, soil survey data, and cropland
data) are widely used in many research areas, ranging from agricultural sustainability, food
security, and biodiversity, to natural resources monitoring, disaster assessment, carbon and
accounting bioenergy”(Han et al., 2014). Thus, the information plays an important role in
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 80
agricultural production(Y. Q. Huang et al., 2012) and decision as well as policy making. The
information is produced by various organizations. Therefore it has different data formats and
specifications thus making it difficult to integrate and share (Y. Q. Huang et al., 2012). In this
situation, users can not make use of the information at different spatial scales for agricultural
assessment and analysis(Yang et al., 2011).
The critical review of scientific literature indicates that spatial data of various kinds is
required for sustainable agriculture, agricultural policies and practices. For understanding the
local agricultural context of a region and to predict precisely requires accurate “geospatial
data on land use, productivity, soils, climate, water availability, institutions, and so on”
(Norton, 2016). Information and education are critical for the policy makers, farmers and
consumers to make appropriate policy (Government of Pakistan, 2018c).
8.1 Importance of Data for Policy-Making
Information and education are critical for the policy makers, farmers and consumers to make
appropriate policy (Government of Pakistan, 2018c). Baumgartner and Jones (2015) explored
the role of information in public policies. They argue that, “To understand a complex issue,
governments must gather information about the issue”. They further suggest two types of
information: entropic information and expert information. Entropic information, which can be
described as incorporating ‘diverse viewpoints into a decision-making process’ (p. 78), is a
good fit for problem discovery, while expert information is useful for problem’s solution.
While highlighting the need of more information gathering, they find that, “the more
information one gathers, the more one understands the multidimensional character of the
issue, and the more one might be tempted to create a range of public policy programs
designed to address different elements of [the problem].
They define relationship between information and public policy as, “Information is critical
for problem solving, and hence how governments recognize, organize, and respond to
information is essential to understand public policy, the outputs of government activities”.
8.2 Role of Spatial Information within Policy-making
Monmonier (1982) argue that map is the principal medium for communicating geographic
information. According to him, map-making (cartography) is a policy science. He notes that
most of the maps are made by governments and enormous amounts are spent by governments
and private firms for the collection and presentation of spatial data. He argues the role of
cartographers as individuals in map making “but the important decisions are institutional—
federal, political or corporate, rather than individual”. He highlights that “It is the information,
not the map, that will be the principal product, and it is the agency or information network,
not the map-maker, that will be the primary provider”. He underpins, “in communicating
geographic information, public policy is a more significant factor than the eye-brain system”.
He asserts that “if the information is not collected, organized, and disseminated, then the best
design talent and the most astute theories of graphic communication are of no avail”. He
argues that major constraints to collection, organization and dissemination of GI are
institutional and political, not technical in nature.
While discussing cartography as a policy science, he stresses the need to understand
“institutional aspects of information management’. According to him, “…policy specialists in
economics study and debate government and private-sector programmes to increase
employment and productivity, so too are policy specialists in geographic cartography needed
to evaluate the effectiveness of public and private efforts to collect, organise and disseminate
geographic information”. He recognized the need of policy makers and scientists for better
information and to “evaluate the effectiveness of public and private efforts to collect, organise
and disseminate geographic information”. He points out that, “Cartographers and geographers
have a stake in policy science, for in the same sense that there is need for a policy on energy
81 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
and natural resources, there is need for a policy on mapping and geographic information.
Geographic information has the potential of becoming a major pillar of modern (Monmonier,
1982) public policy making process. A policy oriented geographic information concentration
has much (Monmonier, 1982) to do with policy making process.
Coppock (1974) grasped the reality of increasing awareness about spatial dimensions
of public policies. He argues, “it is highly appropriate to consider the role of geography [and
geographic information] in policy-making”. He further sheds light on the crucial fact that
policy makers themselves generally don’t have awareness regarding the spatial dimensions of
the problems or policies that may be due to the reason that geography get relatively low
importance in the academic institutions. According to him, “Understanding policies and
processes of decision-making is thus essential to an understanding of the contemporary
geography”. It is also important to have “the ability to analyze the spatial dimensions of the
problems and, more particularly, to handle, analyze and interpret spatially distributed data”.
In agriculture, resource management is significantly important and it has a spatial dimension
according to (Coppock, 1974). Geographic information can help to understand, identify and
mobilize the necessary resources according to local needs of the various regions. He finds
that spatial dimension is a major ingredient of all problems and resource management. To
offer solution for the large-scale projects which policy-makers face require handling of large
quantities of data, he concludes.
The implementation of GIS--coupled with a rigorous approach to information
management- provides the public sector with a significant opportunity to improve the
effectiveness of policy and the efficiency of programmes (Worrall & Bond, 1997).
Geographic information is critical to promote economic development, improve our
stewardship of natural resources and to protect the environment. Modern technology now
permits improved acquisition, distribution, and utilisation of geographic (or geospatial) data
and mapping. The National Performance Review has recommended that the Executive Branch
develop, in cooperation with State, local and tribal governments and the private sector, a
coordinated National Spatial Data Infrastructure to support public and private sector
applications of geospatial data in such areas as transportation, community development,
agriculture, emergency response, environmental management and information
technology(Coordinating Geographic Data Acquisition and Access, the National Spatial Data
Infrastructure, Executive Order 12906, Federal Register 59,17671-17674, 1994).
Harris & Hooper (2004) assessed through textual analysis, the concept and practice of ‘spatial
planning’ in the context of the formulation of public policies in Wales providing a spatial
context for major development decisions and for the allocation of resources. They reviewed
various sectorial policy documents published by the National Assembly of Wales for spatial
content. They concluded that “a spatial planning approach, if successfully developed and
enhanced, offers real value in the development of public policy” whereas “space and place are
in fact relevant and significant in the development of public policy”.
Barjolle, Sylvander, & Thévenod-Mottet (2011) find that GI has been instrumental in
EU common agricultural policy (CAP) and rural development. They argue, “Producers [of
agricultural products] may be at an advantage or a disadvantage by virtue of their
geographical location and their proximity to consumer centres”. They note, “for adjusting
supply and demand on generic markets for agricultural commodities, states have set up [GI]
systems for sector regulation in the context of their agricultural policies”.
Simukanga, Muhone, Mulenga, Phiri, & Nyirenda (2018) implemented an agricultural
geographical information system in South Africa. They argue that, “By understanding
geography and people’s relationship to location, we can make informed decisions”. They
highlight the importance of GIS and spatio-temporal data for policy makers, “Researchers and
policy makers may integrate spatial, temporal, and socio-economic data [using GIS] in order
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 82
to get better manageability, higher and quality productivity”. They note that reliable crop
information is essential for informed decision and policy making.
Huang, CHEN, YU, HUANG, & GU (2018) assessed available remote sensing data resources
for precision agriculture. They described and adapted a five-layer-fifteen level (FLFL)
satellite remote sensing data management structure for precision agriculture. They argue,
“The key of agricultural remote sensing is, with global positioning data and geographic
information, to produce spatially-varied data for subsequent precision agricultural
operations”.
8.3 Spatial Data for Agricultural Policies
Geospatial data and technologies are being widely used because of their capability to improve
development and planning of a nation(Majeed & Hanafiah, 2018). Masser (2007) underlines
the importance of location as a key factor in policy making. He argues that spatial databases
need to be assembled and made available at the national level for informing national policies.
The role of better data for better policies is also endorsed by (FAO, 2014b).
The spatial data required for agricultural policies can include the following:
Geospatial data
Precision agriculture demands collection, storage, sharing and analysis of large amounts of
geospatial data(Nash et al., 2009). Geospatial data coupled with web and mobile application
can help policymakers to understand, visualize and analyze the impact of agriculture on the
environment(Kamilaris et al., 2018). Geospatial data includes topographic data that is used as
base map to integrate various kinds of thematic information such as soil, rainfall and
population. Geospatial data can include satellite imagery, too.
Hydrological data
Rehman et al. (2019) identified three major factors impeding agricultural productivity in
Pakistan including water availability. Hydrological data helps to understand the potential
availability of water to crops, livestock and fisheries etc. Agriculture is usually the applicant
for water(Norton, 2016). Therefore, hydrological data relates to water resources such as lakes,
rivers, irrigation channels, wells and tube wells etc.
Digital Elevation Model (DEM)
Digital elevation model (DEM) plays an important role in agricultural planning such as
extraction of drainage networks(Wu et al., 2019), cultivation planning(Jasinski et al., 2005)
and appraisal of agricultural lands(Sakai & Chikatsu, 2008).
Cadaster (Land ownership) data
Information related to the location, size, boundaries and ownership of land parcels comes
under this category. This is important to know who owns a land parcel so that necessary
agricultural inputs can be delivered to the right person. Moreover, land ownership information
can be effectively used to allot land to agrarians who donot own agricultural land but possess
formal education in agricultural sciences(Elahi et al., 2020). For example, in 2009, the
Government of Punjab significantly increased the yield of major crops such as wheat, rice,
cotton, and sugarcane by 16.5, 14.2, 12.3, and 23.2%, respectively by allotting land to
agrarians (Elahi et al., 2020). Having land ownership information will be helpful to get back
state land encroached by people and therefore contribute towards timely and better
management of agricultural land(Elahi et al., 2015; Jehangir et al., 2007; Jiang et al., 2017; Li
et al., 2017). Also, governments from time to time announce subsidies on agricultural inputs
such as seeds, pesticides and fertilizers etc for farmers. Therefore, having land ownership
information would be helpful in implementing and informing agricultural policies.
Land use data
Land use data helps to identify the human activity or economic function on a specific piece of
land, e.g. urban use, industrial use, etc. In Pakistan, due to non-existence of dedicated land use
system, changes in land use are occurring almost every day and there are ambiguities in the
83 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
existing policies in defining different forms of formally and informally recognized land rights
(A. Ullah et al., 2020). Therefore, there is dire need to have data on land use in the country.
Data regarding actual use of land such as agricultural, residential, commercial etc. This type
of data helps to determine the magnitude of land being used for agriculture and therefore
helps to understand the pattern of increasing or decreasing agricultural land in a region. The
data can be helpful to analyze the required resources such as water, energy and physical
infrastructure for the development of agriculture in a specific area.
Land cover data
Land cover data is used to identify type of features present on the land. It refers to a physical
property or material, e.g. water, sand, etc.
Remote Sensing
The data captured by remote sensing satellites “assist with the assessment of crop condition
and crop condition anomalies, which can then be used to infer information on yield, area and
production”(Fritz et al., 2019). Similarly, Zhang et al. (2019) finds that “high spatial
resolution (HSR) remote sensing images are a reliable source for classifying urban land use.
Crops data
Data related to location and types of major crops grown is also useful as it helps to
understand, visualize and analyze the area under major crops such as wheat, rice, sugarcane
and maize etc as finds (Ali Chandio et al., 2016).
Research data
Data generated by researchers during their agricultural research is also an important outcome
as the data can be re-used by other stakeholders including but not limited to governments and
researchers. Neylon, (2017) asserts that research data is a quite useful outcome of a research
that can be benefited in some other research studies.
Soil data
Accurate information about soils is required for land resource management, monitoring, and
policy-making(Lucà et al., 2018). Therefore, soil is vital for informed decision and policy
making.
Agricultural census
It includes data such as employment statistics, land utilization, area under important crops,
livestock population, agricultural machinery statistics, crop yields and fertilizer usage as
fertilizers are the main inputs that are used to achieve high and fast rates of agricultural
returns(Rehman et al., 2019).
Weather / meteorological data
In order to predict and advise farmers, weather or meteorological data is of prime importance.
Zhai et al. (2020) argue for the same, “ … meteorological information, soil conditions,
marketing demands, and land uses, can be collected, analyzed, and processed for assisting
farmers in making appropriate decisions and obtaining higher profits”. Data of temperatures,
rainfall, sunshine duration, moisture, humidity, and wind speed can include this category of
data.
Pest and disease data
Pest attacks cause a major damage to agriculture. Chougule, Jha, & Mukhopadhyay, (2016)
find that, “[agriculture decision support systems] ADSSs are able to warn farmers about
possible occurrences of pests and diseases, helping them to take certain precautions to avoid
further losses”. But it requires data on pests and diseases to prevent the potential loss. This
information will also be of great use for companies engaged in preparation of pesticides.
Data on natural hazards
Natural hazards such as droughts, floods and landslides have direct and negative impact on
agricultural productivity. Simukanga et al. (2018) argues for the same, “ [food security] is
affected by factors such as poverty, health, food production, political stability, infrastructure,
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 84
access to markets, and natural hazards”. Therefore, having historical and predicted datasets on
natural hazards can help in mitigation and preparedness efforts while making sustainable
agricultural policies for a specific region.
From the literature cited above, it reveals that various kind of spatial datasets are
needed for evidence-based agriculture policy making. The summary of the key data sets
required is listed in Table 4 and Table 5. Table 4: Main spatial datasets to address agriculture issues
Spatial data References
Geospatial Data Fritz et al. (2019), Kamilaris et al. (2018); Nash et al.
(2009); Khan (2011)
Hydrological data Fritz et al. (2019); Rehman et al. (2019); Norton
(2016); Ali1 & Ahmad, (2012); Padilla-Pérez & Gaudin
(2014); Moro (2016); ADB (2009); Raja (2015); Bai et
al. (2016)
Cadastre (land ownership)
data
Elahi et al. (2015); Jehangir, Masih, & Ahmed (2007);
Jiang et al. (2017); Li et al. (2017)
Land use data A. Ullah et al. (2020), Zhai et al. (2020); Khan, (2011)
Crops data Fritz et al. (2019); Ali Chandio, Jiang, Ali Joyo, &
Rehman (2016);Government of Pakistan (2016); Raja
(2015); Reidsma, Ewert, Lansink, & Leemans (2010);
Bai et al. (2016); Khan (2011)
Research data Neylon (2017)
Soil data Fritz et al. (2019); Zhai et al. (2020); Lucà, Buttafuoco,
& Terranova (2018);OECD/FAO (2016); Reidsma et
al. (2010); Padilla-Pérez & Gaudin (2014)
Agricultural census Fritz et al. (2019); Rehman et al. (2019), Morton
(2007); Padilla-Pérez & Gaudin (2014); Raja (2015)
Weather / meteorological
data
Zhai et al. (2020); Fritz et al. (2019); OECD/FAO
(2016); Khan (2011)
Pest and disease data Chougule, Jha, & Mukhopadhyay (2016)
Data on natural hazards Simukanga et al. (2018)
Remote Sensing Zhang et al. (2019); Fritz et al. (2019); Reidsma et
al.(2010); Khan (2011)
Land cover data Khan (2011); Fritz et al. (2019)
Climate change
Khan (2011); Government of Pakistan (2016);
Government of Pakistan (2015); Fatima & Yousaf
(2014); Dinar, (1993); CCAFS (2016); Shirgure &
Shirgure (2013); Steenwerth et al. (2014); Moro
(2016); ADB (2009); OECD (2015);Zhai et al. (2020)
Impact of Climate Change on agriculture
The negative impact of climate change on agriculture is well acknowledged in theory and
practice. It can cause for example desertification, salinisation, land degradation and soil
erosion, saltwater intrusion due to rise in sea level and flooding. In the context of Pakistan,
following literature was sighted.
Prăvălie (2016) finds that desertification is affecting 38 of 48 countries in Asia and it
is a serious problem in Pakistan (Irshad et al., 2007; Lal, 2018). Major river basins such as
Indus Basin in Pakistan is undergoing salinisation (Aslam & Prathapar, 2006). In Pakistan,
about 6.2 Mha of agricultural land is affected by salinity(NIAB, 1997). Land degradation
affects people and ecosystems throughout the planet and it is a driver of climate
change(Shukla et al., 2019, p.53).
85 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Saltwater intrusion is also one of the problems being faced in coastal areas of
Pakistan. The Indus Delta, located near Karachi is an example of seawater intrusion and land
degradation due to climatic and environmental conditions(Rasul et al., 2012). Salinisation and
waterlogging in the provinces of Punjab and Sindh is due to over-irrigation (Chandio et al.,
2011).
Agriculture in Pakistan has been negatively affected by climate change(Shukla et al.,
2019, p.452). Abbas et al. (2017) finds that from 1980 to 2014, there is an average shift of 4.6
days per decade earlier in the case of spring maize growing periods whereas sowing of
autumn maize has been delayed 3.0 days per decade. Similarly, Tariq et al. (2018) found that
due to rise in temperature from 1980 to 2016, there are shifts in sowing, emergence, anthesis,
and maturity for fall and spring crops.
In developing countries, floods negatively impact access to food and livelihoods. In 2010, the
unprecedented rainfall in Indus valley of Pakistan led to flooding, affecting the lives and
livelihoods of 20 million people. There is evidence that these effects were due to climate
change (Mann et al., 2017). Accordingly, the food prices were high causing more food
insecurity in the country(Shukla et al., 2019,p.516).
From above cited literature it reveals that climate change is the major threat to agriculture.
Therefore, it needs a special mention. Location information (spatial data) typically plays an
important role in climate change studies(Below et al., 2015; Hinkel, 2011; Tiwari et al., 2008;
Vincent, 2007). Paudyal, Dev Raj and McDougall, Kevin and Apan (2011) in their research
identified main spatial datasets to study climate change in a region.
Table 5: Main spatial datasets to address climate change
(Source: Paudyal, Dev Raj and McDougall, Kevin and Apan, 2011)
Spatial Data Local State National
Atmospheric ×
Climate × ×
Land Use/Land Cover
Digital Elevation Model × ×
Demography/Population
Distribution × ×
Soil and Geography ×
Aquifer and Ground Water × ×
Surface Water ×
Watershed/Catchment × ×
Landownership/Cadastre ×
Infrastructure × ×
Protected Areas × × ×
Source of Pollution × ×
Topographic base ×
Ariel Photograph/Orthophoto ×
Buildings ×
Transport × ×
Air Quality × ×
Ecosystems Zones × ×
Vegetation ×
Rainfall × ×
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 86
From Table 4 and 5, it reveals that 25 spatial datasets of various kinds are required to
address issues faced by agriculture. Practically, it is impossible for a single organization to
collect, maintain and provide these datasets due to mandate constraints. But it does not
include datasets required for agricultural monitoring and land management which is described
next.
For agricultural monitoring
Fritz et al. (2019) in their recent study compared eight main global and regional agricultural
monitoring systems based on the input data and models being used. They identified forty
thematic datasets required for agricultural monitoring. The authors found fundamental gaps in
the data and data collection methods. Accordingly, they suggest to harmonize data collection
methods.
Figure 4: The level of importance of datasets for agricultural monitoring
Source: Fritz et al. (2019)
For land management
Erb et al. (2017) from an inventory of the main data sets available for different land
management practices, found that ten various kinds of datasets are crucial for land
management in order to understand and address the “global sustainability challenges such as
climate change, biodiversity loss and food security”. The datasets include forestry harvest,
tree species, grazing and mowing harvest. crop harvest and residue management, crop species,
N-fertilization, tillage, irrigation and wetland drainage, and fire management.
9. Inventory of necessary spatial datasets for agriculture: The synthesis
To synthesis all the above mentioned spatial datasets, Table 6 lists all the necessary spatial
datasets required for agricultural practices and policy-making. The table also mentions user
as well as producer organizations of the datasets in Pakistan.
Table 6: Use–produce–origin description for types of geographic information necessary for
agricultural policies
(adapted from Chantillon et al., 2017)
Type of data Description Use—Produce—Origin
Hydrological Data (It is the data regarding
water resources)
• 9 user organisations
• 4 producing organisations
87 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Type of data Description Use—Produce—Origin
• The data mainly originate from Water and
Power Development Authority (WAPDA).
Cadastre (land ownership) Data
(It is the data which defines the geographic
extent of the past, current, and future rights
and interests in real property and the spatial
information needed to describe that
geographic extent)
• 7 user organisations
• 4 producing organisations
• The data mainly originate from the
provincial governments.
Land Use Data
(It is the data which tells us about the human
use of land. Land use involves the
management and modification of natural
environment or wilderness into built
environment such as fields, pastures, and
settlements)
• 7 user organisations
• 5 producing organisations
• The data mainly originate from the
provincial governments.
Crops Data (It tells us about the useful
information regarding crops maps, crop
intensity and crops management)
• 4 user organisations
• 5 producing organisations
• The data mainly originate from the
provincial governments.
Research Data (It tells us about the
information that has been collected, observed,
generated or created to validate original
research findings)
• 1 user organisations
• 18 producing organisations
• The data mainly originate from the
academic institutions.
Soil Data (It tells us about any information
regarding the soil and their types)
• 20 user organisations
• 4 producing organisations
• The data mainly originate from the
provincial governments.
Agricultural Census Data (The Census of
Agriculture is a census conducted that
provides the only source of uniform,
comprehensive agricultural data)
• 15 user organisations
• 5 producing organisations
• The data mainly originate from the
provincial governments and is consolidated at
the federal level.
Weather / Meteorological Data (The weather/
meteorological data provides us the useful
information regarding weather conditions and
also the changes in them)
• 10 user organisations
• 1 producing organisations
• The data mainly originate from the Pakistan
Meteorological Department.
Pest and Disease Data (This data give
information regarding any animal or plant
detrimental to humans or human concerns,
including crops, livestock and forestry,
among others)
• 4 user organisations
• 1 producing organisations
• The data mainly originate from the
Natural Hazards Data (It is the data regarding
the natural disasters including floods,
droughts and land sliding)
• 10 user organisations
• 5 producing organisations
• The data mainly originate from the
provincial governments and National Disaster
Management Authority (NDMA).
Remote Sensing Data (Remote sensing is the • 5 user organisations
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 88
Type of data Description Use—Produce—Origin
science of obtaining information about
objects or areas from a distance, typically
from aircraft or satellites)
• 1 producing organisations
• The data mainly originate from Space and
Upper Atmosphere Research Commission
(SUPARCO).
Land cover Data (Land cover data documents
how much of a region is covered by forests,
wetlands, impervious surfaces, agriculture)
• 7 user organisations
• 1 producing organisations
• The data mainly originate from Space and
Upper Atmosphere Research Commission
(SUPARCO).
Digital Elevation Model Data
(It represents the relief of a surface between
points of known elevation)
• 10 user organisations
• 1 producing organisations
• The data mainly originate from Space and
Upper Atmosphere Research Commission
(SUPARCO).
Demography/Population Data
(Data collected about the characteristics of
the population, e.g. age, gender and income)
• 15 user organisations
• 1 producing organisations
• The data mainly originate from Pakistan
Bureau of Statistics (PBS).
Distribution Data
(The distribution of a statistical data set (or a
population) is a listing or function showing
all the possible values (or intervals) of the
data and how often they occur i.e. temporal
aspects)
• 15 user organisations
• 1 producing organisations
• The data mainly originate from Pakistan
Bureau of Statistics (PBS).
Aquifer and Ground Water Data
(Aquifer/Ground Water Data is all the
groundwater present in the area)
• 10 user organisations
• 1 producing organisations
• The data mainly originate from Water and
Power Development Authority (WAPDA).
Surface Water Data
(It tells us about the water over the surface of
the earth)
• 10 user organisations
• 1 producing organisations
• The data mainly originate from Water and
Power Development Authority (WAPDA).
Watershed/Catchment Data
(The Catchment data/watershed data tells us
about the area from which a city, service or
institution attracts a population that uses its
services)
• 10 user organisations
• 1 producing organisations
• The data mainly originate from Climate,
Energy & Water Research Institute
(CEWRI).
Infrastructure Data
(Infrastructure data informs about
fundamental physical facilities and systems
serving a region such as telecom, transport
and health facilities)
• 5 user organisations
• 1 producing organisations
• The data mainly originate from Planning
Commission of Pakistan.
Protected Areas Data
(Protected areas give information about the
locations which receive protection because of
their known natural, ecological or cultural
values)
• 10 user organisations
• 4 producing organisations
• The data mainly originate from the
provincial governments.
Source of Pollution Data • 4 user organisations
89 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Type of data Description Use—Produce—Origin
(It gives information about the three sources
of pollution; mobile, stationary and area
sources. For example, cars, buses, planes,
trucks, and trains are moble sources of
pollution. Stationary sources can include
power plants, oil refineries, industrial
facilities, and factories. Area sources include
agricultural areas, cities, and wood burning
fireplaces)
• 1 producing organisations
• The data mainly originate from the
Ministry of Climate Change.
Topographic Base Map Data
(Topographic data are information about
natural and man-made features that appear on
the earth)
• 30 user organisations
• 1 producing organisations
• The data mainly originate from Survey of
Pakistan (SoP).
Ariel Photograph (It is airborne imagery) • 4 user organisations
• 1 producing organisations
• The data mainly originate from Survey of
Pakistan (SoP).
Buildings Data
(It refers to the characteristics of buildings)
• 5 user organisations
• 4 producing organisations
• The data mainly originate from provincial
governments.
Transport Data
(It is the data related to the means of
transportation)
• 20 user organisations
• 6 producing organisations
• The data mainly originate from Survey of
Pakistan (SoP).
Air Quality Data
(It indicates how clean or unhealthy air is in a
region)
• 5 user organisations
• 1 producing organisations
• The data mainly originate from Ministry of
Climate Change.
Ecosystems Zones Data
(It deals with the precipitation intensity,
variability and annual amounts across a
region)
• 4 user organisations
• Could not be specified.
• Could not be specified.
Vegetation Data
(It refers to type of plant)
• 10 user organisations
• 5 producing organisations
• The data mainly originate from
SUPARCO.
Rainfall Data
(It is the data regarding rainfall)
• 15 user organisations
•1 producing organisations
• The data mainly originate from Pakistan
Meteorological Department.
Agricultural Production Data
(It refers to the production of agricultural
crops)
• 15 user organisations
• 10 producing organisations
• The data mainly originate from the
provincial governments.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 90
Type of data Description Use—Produce—Origin
In Situ Measurements
(These are measurements that are made on
ground)
• 32 user organisations
•5 producing organisations
• The data mainly originate from Survey of
Pakistan.
As shown in Table 6, thirty (30) types of geographic information is necessarily
required for agricultural policy-making. It is also evident from the table that several
organizations at various spatial scales ranging from national to local level are engaged in
producing the information. The number of user organizations of the information are up to 32
in certain cases. This scenario calls for implementation of national spatial data infrastructure
(NSDI) for efficient management and sharing of the data to inform agricultural policies and
practices.
10. Conclusions and recommendations
Agriculture in Pakistan, “despite its falling share in national income, continues to attract
considerable attention in policy debates because of its strategic importance to the livelihood of
farming communities, poverty reduction and national food security”(Birthal et al., 2020). The
literature cited and discussion made so far in this chapter reveals that agriculture in Pakistan is
facing several issues such as low availability of water, low productivity, deprived physical
infrastructure, food insecurity, degradation of natural resources (land, water), outdated
cultivation methods, issues with supply of agricultural inputs and lack of adoption of the latest
technology coupled with climate change threats. This situation calls for sound decision and
policy making at national and provincial levels. For evidence-based decision and policy
making, spatial data is an indispensable element. But finding the 30 spatial datasets (see Table
6) that are consistent and compatible is problematic(Ackrill, 2000, p.80). The timely
availability of spatial information can impact directly and positively agricultural policy-
making. From an agricultural policy perspective, governments have to prioritize resource
mobilization such as seeds, fertilizers and pesticides in the first place. In the second place,
establishment of physical infrastructures such as transportation, water and food storage
infrastructure should be setup in order to overcome postharvest losses. For resource
mobilization, developing physical infrastructures and studying the impact of agricultural
policy (Scozzafava, 2008) access to spatial data of various types is a pre-condition. In this
background, the study proposes the establishment of spatial data infrastructure (SDI) as the
means to assemble and share geographic information held by various organizations for
effective and evidence-based policy making including but not limited to agriculture.
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Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 102
Assessing the Reform Options of the Public Pension Scheme of the Republic
of Cyprus1,2
Abstract:
Empirical evidence had revealed that the public pension scheme of the Republic of Cyprus (as
it was functioning and before its reform into its current situation), could generate undesirable
and widely distributed economic impacts. This study, focuses on examining alternative
reform scenarios aiming to identify the possible reforms of the public pension scheme as well
as the required extend of the reforms in order to enhance the financial sustainability of the
Public Pension Scheme. The suggested reform options include parametric changes to the
providences of the scheme such as increasing the financial contribution of the civil
employees, extending the retirement age, decreasing benefits and modifying the methodology
for determining the level of pensions as well as for readjusting pensions. The objective of this
research project, is to identify the reform options of the Public Pension Scheme of the
Republic of Cyprus, that can enhance the sustainability of the public pension scheme and of
course to keep both parties, the government and the civil servants, satisfied. The paper
concludes that effective institutional intervention with the suggested reforms can enhance the
sustainability of the public pension scheme and will benefit the budgetary balance of the
Republic of Cyprus. Finally, the paper concludes and gives some suggestions for further
research.
Keywords: Republic of Cyprus; public pension scheme; reform options; economic impacts.
JEL: H55 - Social Security and Public Pensions
Charalambos N. Louca3, George M. Korres4 and George O. Tsobanoglou5
1 Acknowledgments: Our sincere thanks to the Research Promotion Foundation for funding the research project,
“Sustainability and Modernization of the Public Pension Scheme of the Republic of Cyprus”. We thank the
Muhanna and Co. Actuarial Services, for their valuable contribution to the research project, as well as the
Administrations of the American College and of the University of the Aegean for their support. Thanks to the
Treasury of the Republic of Cyprus as well as to the Department of Public Administration and Personnel for
their support throughout the research project. 2 In memory of our beloved friend and scientific partner,
Mr. George M. Psaras, FCAA, Managing Actuary, Social Insurance, Pension and Provident Funds, Muhanna and
Co. Actuarial Services.
Note: This research project was completed in 2008 but the results pointing out the suggested reform options
were not published. This is the first time that they see the light of publicity. 3 Corresponding-Address: Associate Professor Dr. Charalambos N. Louca, Associate Professor, Head of
Business Department and Director of Research Department, American College, Eleftheria Square, P.O.Box
22425, Nicosia, Cyprus. Tel: +357 22 36 80 00, Fax: +357 22 36 80 01. Email: [email protected] 4 Corresponding-Address: Professor Dr. George M. Korres, Professor, University of the Aegean, School of
Social Sciences, Department of Geography. Email: [email protected] 5 Corresponding-Address: Professor Dr. George O. Tsobanoglou, President, International Sociological
Association, Research Committee on Socio-technics & Sociological Practice (ISA-RC26). Professor, University
of the Aegean, Department of Sociology. Email: [email protected]
103 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
1. Introduction
The public pension scheme of the Republic of Cyprus provided supplementary retirement and
widow pensions to government employees. It was almost entirely financed by the general
taxation system, since participation of employees in the financing of the public pension
scheme was limited to 0.75% contribution rate of their gross earnings, to pay for widows’ or
survivors’ pension. A brief description of the public pension scheme before the reforms of
2011 are applied is given below.
Early retirement was allowed from the age of 45 but the pension was frozen and
could only be paid at the age of 55 (at the age of 58 for government employees who joined
employment on or after the 1st of July, 2005) without any actuarial reduction of benefits. The
mandatory retirement age for the civil servants was the 63rd year of age and the 60th for the
teachers. Retirement for the police force, was the age between 60 and 61, for the employees in
the army the 52nd and the 60th year of age depending on the position and the rank of the
people in the army.
The pension was calculated on the basis of the final salary at an accrual rate that produces
a retirement benefit equivalent to 50% of that salary after 33 1/3 years of service or 400
months.
A lump sum gratuity was paid when an employee retired and is a multiple of the annual
pension. Today the maximum coefficient of the lump sum is 15/3 of the annual pension.
The Public Pension Scheme of the civil servants exercised substantial pressures upon
the public economics of the Republic of Cyprus. In 2006 the expenditures of the Scheme were
2.2% of the GDP and it was expected that by 2040 to be 2.8% of the GDP. According to
Eurostat (2015), the total expenditures on pensions including pensions of government
employees, was 10.8% of the GDP. In case that the expected rate of GDP is not attained, then
the cost of the Public Pension Scheme can fluctuate between 2.8% and 4.5% of GDP (table 1).
An expenditure of 2.8% of the GDP implies an average pay-as-you-go cost of 32.7% of the
wage bill. This by far exceeds the contributions of the public employees, which were only
0.75% of the wage bill, before the reforms of the scheme were applied in August 2011. After
August 2011, the employees’ contributions had risen to 5.1% of the wage bill.
Table 1: Cost Sensitivity of the Scheme Relative to the Increasing Rate of GDP
Projections of GDP, increasing by a lower percentage
rate than the rate before the economic recession of
2013
Long-term
Expenditures of
the Scheme as a %
of GDP
Projection of GDP – According to the Ministry of Finance
(before the economic recession of 2013)
2.8%
Projection of GDP by 0.5% lower increasing rate 3.3%
Projection of GDP by 1% lower increasing rate 3.9%
Projection of GDP by 1.5% lower increasing rate 4.5%
Source: Louca, Ch., Korres, G., Tsobanoglou, G. and Kokkinou, A. (2011)
The present value of the accumulated pension benefits of the current pensioners and
of the civil employees is estimated to be 8.34 bil Euros. If it were to develop an independent
fund for covering pensions, this should be endowed with an amount of 8.34 bil Euros, plus a
long-term financial contribution of 37% of the retirement remunerations (Louca, et al 2011).
What had leaded to high expenditures of the scheme can be identified in the following:
The civil servants did not contribute to the Scheme. Their contribution of 0.75% of the
wage bill, was supposed to cover the 50% of the cost of the widow pension.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 104
The pensions were revised based on the inflation rate and on the general wage rises given
to the employed civil servants.
The retirement age did not rise to the 63rd year of age for all the civil servants. Currently,
for the majority of the government employees the retirement age, is the 65th year of age.
Other problems identified, can be the early retirement without any actuarial decrease in
pensions.
Changes in the above mentioned issues could decrease the annual expenditures of the
Public Pension Scheme of the Republic of Cyprus and secure its long-term sustainability.
Currently in the Republic of Cyprus, there is a continuous trend towards reforming the
public pension Scheme of the government employees. The reforms aim at reducing the cost of
the system to the government and at improving equity between the civil servants and the
employees of the private sector. Reforms can be both parametric and structural. The
parametric reforms to the Public Pension Scheme that this paper, studies are:
(a) the permanent contribution rate of public employees, to increase from 0.75% to 5.1%
of the wage bill; and
(b) the indexation of pensions to be based only on inflation.
This paper, aims to identify and suggest additional possible reforms of the Public Pension
Scheme of the Republic of Cyprus so that to guarantee its sustainability. The suggested
reforms are based on the actuarial projections presented in the paper, “assessing the public
pension scheme of the Republic of Cyprus” (Louca, et al 2011).
Thus, the objectives of the study are:
1. To identify the possible reform options of the Public Pension Scheme of the Republic of
Cyprus that can enhance the financial sustainability of the scheme and improve growth
prospects in Cyprus.
2. To assess the impacts of these reform options on the actuarial liability, on the long-term
total expenditures as a % of GDP in prices of 2007, on the normal contribution rate and on
the pay-as-you-go-cost for the period 2007 – 2070.
For achieving these objectives, the main actuarial projections under the existed
arrangement are firstly presented. Secondly, possible simulation scenarios of the demographic
and financial assumptions considered are studied. Finally, based on the simulation scenarios
studied, possible reform options of the Public Pension Scheme of the Republic of Cyprus are
proposed.
Following this section of the paper, a brief literature review is outlined, the
methodology applied follows as well as the demographic and financial assumptions that are
taken into consideration in the projections of the study are presented. Then the main projected
positions under the existed arrangement are presented, including projections of the fiscal
stance and the liabilities. The outcomes of the simulation scenarios of the assumptions
considered are then presented. In the next section, based on the outcomes of these simulation
scenarios, possible reform options to the scheme are proposed. The paper, finally concludes
and gives some suggestions for further research.
2. Literature Review
The European Commission, faces the challenge of delivering adequate and sustainable
pensions in Europe (European Commission, 2010 and European Commission, Economic and
Financial Affairs, 2017).
Countries in the EU such as France, the United Kingdom (Ex EU member), Finland,
Sweden, Germany, Italy, Austria, Greece, Portugal, Spain, the Netherlands, Belgium and
Dania have reformed their public pension schemes before other member countries of the
European Union.
Academics very early have shown interest in reforming social insurance systems.
Specifically, Prof. Barr, N. (2000), Diamond, P. (2002), Barr, N. and Diamond, P. (2009),
105 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
have determined the requirements for reforming pensions and have developed guidelines for
governments that would like to proceed with reforms to their pension systems. Cogan, F. and
Olivia S. Mitchel (2002), have proposed to the EU a system of dual arrangement. Palacios, R.
and Whitehouse, E. (2006) have studied the public pension schemes of civil servants in
different countries as well as the reforms of the public pension schemes in those countries.
Capretta, C. (2007), has studied the impacts of the population ageing on the sustainability of
the pension schemes of the civil servants in twelve economic developed countries.
3. Methodology
For achieving the objectives of the study, two software were developed; one for projecting the
income and expenditure of the Scheme and one for estimating the cost of the actuarial liability
of the Scheme.
The first software aims to project the cash flow of the Scheme for the next fifty
years. This software assesses the long-term financial situation of the Scheme and examines
the ratio of income to expenditure (Cichon, 1999). This method is mostly used for schemes
which are not fully funded.
The second software aims to estimate the cost of the Scheme and its actuarial
liability (American Academy of Actuaries, 2004) at the date of the estimation. This method is
mostly used for schemes which are fully funded.
3.1. Software for projecting income and expenditure
For estimating the income and expenditure of the Scheme we firstly proceeded with the
demographic and financial projections. The demographic projections include: (a) projection of
the employed civil employees covered by the Scheme; (b) projection of the retired civil
employees; and (c) projection of the widows and orphans.
The financial projections include: (a) projection of wages; (b) projection of employment of
the civil employees; and (c) Projection of benefits.
3.1.1. Demographic projections
(a) Projection of the employed civil employees covered by the Scheme
The projection of the number of insured employees is based on:
the expected number of the insured members of the Scheme in each year;
the number of the insured employees of the previous year who are expected to remain
insured;
the number of the new insured employees who enter the Scheme; and
the expected age distribution of new employees for every year.
(b) Projection of the retired civil employees
The projection of the number of the retired civil employees is based on:
the expected mortality which differs by age and sex; and
the expected probability of new members to retire (according to age as well as sex in
each year, due to the long-term assumption that the retirement age is increased to the
63rd year for certain categories of civil servants).
In appendix A, table 2, the data of the retired employees in 2006 is presented which is used
for projecting the number of the retired employees in the Scheme.
(c) Projection of widows and orphans
The projection for the beneficiaries of widow pension is based on:
The expected mortality which depends on age; and
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 106
The expected mortality of the married insured employees and pensioners. These changes
according to age and year, are used for the projection of the number of the widow
pensioners of the scheme.
3.1.2 Financial projections
The projection of wages depends upon the wage level of the employees at the date of their
retirement. Therefore, the second part of the software covers, (a) the projection of wages
based on the assumptions presented at the end of this section in table 3; (b) the projection of
the period of employment of the civil employees; and (c) the projection of benefits.
(a) Projection of wages
The projection of the average wage at each age level depends upon the estimated rate of wage
rise which is expected during the period of the projection. Specifically, the projection depends
upon:
the general wage rises;
the wage-rises due to inflation; and
the wage-rises due to service and promotion.
(b) Projection of the period of employment of the civil employees
The benefits received are directly related to the period of employment of the civil servants.
Based on data received from the Department of Public Administration and Personnel of the
Ministry of Finance, the future expected service until retirement is estimated.
(c) Projection of benefits
The demographic projections in combination with the projection of wages and the projection
of the period of service are used for the projection of benefits. Specifically, the projection of
the retirement pension includes the following two components:
The pension paid to the current retired pensioners. This is the pension paid during the
previous year and readjusted based on the rate by which pensions rise and according to
the relevant mortality.
The pension paid to the new retirees.
In the projections the benefit received as a supplementary pension from the Social Insurance
Fund is considered as well.
3.2 Software for estimating the actuarial liability
According to the provisional Law for establishing, registering, functioning and supervising
pension funds, the actuarial liability is estimated for fully funded funds. The Public Pension
Scheme of the Republic of Cyprus is not in this category but for the objectives of the study
both the actuarial liability and the cost of the Scheme are estimated.
The actuarial liability is the present value of the benefits which correspond to the
service of the members of the Scheme and have been earned by the date of the estimate.
Normal contribution rate is the percentage rate of contribution which is necessary to
cover the cost of the benefits for the service after the estimation date.
The difference between the actuarial liability and the assets of a fund is the actuarial
surplus or deficit.
According to the International Financial Reporting Standards (IFRS 19), the method
used for financing the fund must be the Projected Unit method (Matt Smith, 2005). It is
“Projected”, because it takes into consideration the projected assumptions until retirement in
estimating the value of the benefits. It is “Unit”, because it studies the cost of a one-year
107 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
future employment. The method presumes that the Fund will continue to accept new members
(Table 2).
Table 2: Entry of New Members into the Scheme
Age Distribution Percentage of New Employees in the
Pension Scheme in each Age Group
< 20
20 – 25
25 – 30
30 – 35
35 – 40
40 – 45
45 – 50
50 +
0.00%
20.00%
46.00%
17.50%
9.00%
5.75%
1.75%
0.00%
Total 100.00%
The method used, differentiates also the benefits that have been accumulated until the
date of the estimation (and the capital/provident that has been accumulated in order to cover
these benefits) from the benefits that will arise as a result of the future employment. The first
group of benefits emerges from the actuarial liability and the second group of benefits
emerges from the normal rate of contribution that must be paid in order to cover the cost of
benefits that will arise from future employment.
The main long-term financial objectives of the Fund are:
to secure that the available capital is sufficient to cover the value of the benefits for the
service that has been already offered, taking into consideration the projected final
wages; and
to secure that the normal rate of contribution is sufficient to cover the benefits that will
arise from the future service.
The Actuarial estimation is carried out in three stages as explained below:
(a) Stage one – Past service
The first stage is carried out in order to identify if the accumulated funds at the date of
estimation are sufficient to cover the accumulated benefits (i.e., the benefits that have been
accumulated for the service offered up to the date of the estimation).
The actuarial value of the benefits (actuarial liability) is then compared with the
actuarial value of the accumulated funds.
The objective of this first stage, is to estimate the monetary value of the benefits that
will arise in the future, as a result of the service offered up to the estimation date. This will
enable us to estimate the necessary funds required to cover the value of the benefits that have
been accumulated up to the estimation date. The estimation takes into consideration the wage
rises that will emerge in the future.
Therefore, stage one, determines the value of any difference between the actuarial
liability and the available funds for covering the responsibilities of the Fund.
(b) Stage two – Normal contribution rate
At this second (2nd) stage the normal contribution rate is estimated. This is the contribution
rate which is necessary to cover the cost of benefits for the service that will be offered after
the estimation date. This contribution rate, is estimated for each employee, by differentiating
the present value of the expected benefit that will be accumulated within the year after the
estimation date (taking into consideration any wage rises until the retirement date, the date of
death or the date of withdrawal from the service), from the present value of the annual wage.
This method which is used for financing the Fund, estimates an average contribution rate for
the whole Fund, as a percentage of the total overall wages of the members of the Fund. This
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 108
contribution should be sufficient to cover the cost of the benefits that will be accumulated in
the year after the estimation date.
(c) Stage three – Disposal of the actuarial surplus and financing the actuarial deficit
At this stage the normal contribution must be regulated so that to eliminate any difference
(positive or negative) between the assets of the Fund and the actuarial value of the benefits as
described in stage one. This kind of regulation can take the form of a lump sum paid (or
returned if it is appropriate), during a fixed time period or even the regulation of the normal
contribution rate during an appropriate time period. As was already mentioned, the Projected
Unit Method assumes that the Fund will continue to accept new members. The normal
contribution rate will not be strongly affected if the distribution of the members according to
sex, age and wage is stable. However, the normal contribution rate will be strongly affected if
the distribution of the members, changes substantially from one estimate to another. This may
happen for example either in case that a substantial number of new members enter the Fund or
old members of the Fund leave it (Louca, et al, 2011). For the objectives of the study, the
demographic and financial assumptions given in table 3 are considered.
Table 3: Description of Assumptions
Demographic Assumptions
Mortality
70% of PA90 (Appendix B, table 4)
with a gradual decrease to 50% in the
next 50 years.
Retirement Rate Retirement at normal age with a very
low percentage at early retirements.
Entry Rate of New Members in the
Scheme
Starting rate of 2.5% with a gradual
decrease to 1% in the next 10 years
and a final fixed rate of 0.5%
Entry of New Members According to table 2
Financial Assumptions
Percentage Rate of Investment 5.5%
Salary Increase 7%
Increase on the Basic Salary 4%
Increase in Pensions
Public Pension Scheme: 3.5%
Supplementary Pension from the
Social Insurance Fund: 2%
In the next paragraph the main projected positions under the present arrangement are
presented.
2. Projected Positions Under the Existed Main Arrangement
It was estimated that up to 2017, the employed civil employees will be increasing by 1% per
year and after 2017 by 0.5% per year. The ratio of the employed civil servants to the retired
ones (ratio of protection) is currently 2:1 (Table 4). In the future, it is estimated that the ratio
of protection will decrease because (a) the pension scheme has reached its maturity, (b) of the
decreasing rate by which the civil servants will enter the public service and (c) of the rising
rate of life expectancy.
109 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table 4: Demographic Projections 2007 – 2070
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Employed
civil servants 31,752 32,503 33,123 33,735 35,891 37,723 40,877 42,999 45,244 47,622 50,065
Civil servants
in pension 12,465 12,895 13,448 13,990 16,370 17,735 19,275 24,212 28,285 30,788 33,085
Beneficiaries of
widow/widower
and orphan
pension
2,443 2,571 2,698 2,826 3,507 4,228 5,536 6,347 6,891 7,730 8,677
Ratio of
protection 2.1 2.1 2.1 2.0 1.8 1.7 1.6 1.4 1.3 1.2 1.2
Source: Treasury of the Republic of Cyprus and authors’ projections (Louca, et al 2011)
3.1 Projection of expenditures and GDP
Based on data from the Treasury of the Republic of Cyprus, the long-term projections of
expenditures (pensions and lump sum benefits) given and to be given to beneficiaries, as a %
of GDP (up to 2060) in real prices of 2007 are given in table 5. The projections are estimated
based on the methodology adopted by the Commission of Economic Policy of the EU. The
long-term assumptions are determined by the convergence program of the EU (European
Commission, 2008).
Table 5: Projections of Total Expenditures and Contributions 2007 – 2070 (£ - Cyprus
Pounds, in Millions) 2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
Expenditure
s
187.
4
202.
4
227.
5
243.
7
331.
6
425.
8
733.
6
1,429.
8
2,150.
4
3,220.
3
4,915.
7
Contributio
ns 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Expenditure
as a % of
GDP in
Prices of
2007
2.1
%
2.1
%
2.2
%
2.2
%
2.1
%
2.1
%
2.2
% 2.8% 2.8% 2.9% 2.9%
Source: Treasury of the Republic of Cyprus and authors’ projections (Louca, et al 2011)
Cyprus Pound (£) = € 0.585274
The contributions are for covering the pensions to widows/widowers and orphans.
Up to a wage ceiling and as determined by the Social Insurance Law, the contribution rate is
0.75% of the annual wages. Beyond this wage ceiling the contributions increase to 1.75% of
the annual employees’ wages.
Table 6: Projection of Total Wages (£ - Cyprus Pounds) and of the Pay as you go Cost 2007
– 2070 (£-million) 2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
Annual
Wages
654.6 710.9 760.4 806.7 1,032.9 1,327.5 2,117.2 2,836.5 4,077.5 6,173.4 9,168.1
Pay as
you go
Cost
28.6% 28.5% 29.9% 30.2% 32.1% 32.1% 34.6% 50.4% 52.7% 52.2% 53.6%
Source: Treasury of the Republic of Cyprus and authors’ projections (Louca, et al 2011)
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 110
Table 6, presents the projections of the annual expenditure for wages up to 2070. The
projected values are based on: (a) data from the Ministry of Finance, (b) the assumption for
inflationary wage rise, (c) the general wage rise; and (d) the annual wage rise. The projection
for the pay as you go cost estimated, is the percentage of the current employees’ wages that
would have been necessary to be paid as a contribution within a given year in order to cover
the total annual cost of pensions and benefits of the Public Pension Scheme.vAlthough the
Scheme is financed by the government’s budget, by studying the cost of expenditure as a
percentage of the civil employees’ wages, we get the required contribution necessary to cover
the annual expenditure of the Scheme in case that the pensions were financed by an
independent fund. The mean of the pay as you go cost for the period 2007-2070 is 43.2%.
3.2. Actuarial liability and normal percentage rate of contribution
For achieving the objective of this study, we have estimated the financial situation of the
Public Pension Scheme by applying the pre-financed method assuming that the Scheme is
financed by an independent fund. In such a case, a fund to be able, (a) to cover all the
biometric risks (death, disability and longevity), (b) to guarantee a given return on investment
and (c) to guarantee given defined benefits, must have adequate reserves for covering these
risks.
Based on data acquired from the Ministry of Finance and the Department of Treasury
of the Republic of Cyprus, we estimated the actuarial liability of the hypothetical fund and the
normal percentage rate of contribution that must be paid for covering the benefits of the
Scheme (table 7). These results will be used for comparison with the outcomes of the reform
options of the Scheme studied in this paper.
Table 7: Actuarial Liability as at 31/ 12 / 2006
Actuarial liability for past service 4,882,000,000
Actuarial deficit (Actuarial liability for past and future service
minus the present value of contributions) 7,578,000,000
Normal Percentage rate of Contribution 36.5%
Actuarial liability as a % of GDP 58.2%
Source: Authors’ projections (Louca, et al 2011)
3.2.1. Actuarial liability for past service
The actuarial liability for past service represents the present value of the benefits granted to
the current civil servants based on the years of service until the estimated retirement date plus
the pensions granted to the current pensioners.
The actuarial liability is presented in table 7 and includes the current civil servants and the
current pensioners.
3.2.2. Actuarial liability for future service
The actuarial liability for future service of the current civil servants and the retired ones is
estimated as well. Due to the fact that the future service of the civil servants is taken into
account, it is necessary to deduct the present value of the future contributions of the civil
servants (table 7).
3.2.3. Contribution rate – future service
The normal contribution rate is the percentage rate of contribution necessary to cover the cost
of the benefits given to the civil servants after the estimated date. During the time that the
research was carrying out, the normal contribution rate (according to the study) is 36.5% of
the wages excluding the 13th salary (table 7). According to the method of financing the
Scheme and the assumptions made for this study, the normal contribution rate must stay fixed
111 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
if the age distribution, the sex distribution and the wage distribution also remain stable. The
revised contribution rate which is the sum of the normal contribution rate (36.5%) and the
percentage rate required to finance the actuarial deficit (70.4%), according to the estimates of
this study, is 106.9 % of the total wages.
3.3. Public economics and the financial liabilities of the Scheme
Regarding the wage level of the civil servants, Cyprus was ranked 3rd in the European Union.
According to the report of the Ministry of Finance for the Stability Program (2008), the wages
of the civil employees were 17% of the GDP. However, according to the present study, the
wages are only 7.2% of the GDP. This is so, because only the full-time civil servants are
considered, without taking into account the part-time civil servants. The high wages and the
generous benefits offered by the Public Pension Scheme, substantially increase the cost of the
Scheme and the expected future expenditure.
3.3.1. Current expenditure as a percentage of GDP
In 2006 the GDP in Cyprus was ₤8.380 billions (Central Bank of Cyprus, 2006).
If the Scheme should have been fully-funded, then the actuarial liability should have
been substantial in relation to the GDP of Cyprus.
4. Simulation Scenarios
The outcome of the projections for the future is uncertain and the degree of uncertainty
increases as the projection period increases. For this reason, an analysis of the outcomes of the
possible changes in the economic and demographic assumptions originally considered is
made. These simulation scenarios aim to identify the impacts of any possible changes in the
economic and demographic assumptions considered, on the expenditures and the
contributions of the Public Pension Scheme. The simulation analysis takes into account
changes in inflation and interest rates as well as changes in the mortality rate and the number
of the retired civil servants.
4.1. Impact of Inflation changes
The Scheme’s benefits are estimated on the basis of the last salary of the employee before
retirement. The assumption for salary rises, substantially affects the projections of
expenditures and contributions as well as the actuarial responsibility of the Scheme and the
normal contribution rate. The main assumptions concerning salary rises, are: 2% inflation
rate, 1.5% general salary rises and 3.5% annual salary rises. This gives an assumption for a
total annual salary rise of 7%.
In these scenarios, we assume that the inflation rate can be either 1% higher or 1%
lower. That is, the total annual salary rise, is assumed to be either 6% or 8%.
Also, the inflation rate, affects other financial assumptions such as:
The income of the employees under the General Social Security Scheme;
The pensions of the civil servants under the public pension scheme; and
The supplementary pension from the General Social Security Scheme.
If we assume that the inflation rate is by 1% lower, this will result to a lower actuarial
responsibility by 20%. If the salaries rise by 1%, then the actuarial responsibility will be by
22.3% higher.
In table 8, the results of the simulation scenarios concerning the impacts of a change
in the inflation rate on the actuarial responsibility, on the normal contribution rate and on the
actuarial responsibility as a percentage of GDP are presented.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 112
Table 8: Inflation Impacts
Inflation rate: 1% Inflation rate: 3%
Actuarial Responsibility 4,060,000,000 5,971,000,000
Normal Contribution Rate 27.6% 49.1%
Actuarial Responsibility as a % of
GDP 48.5% 71.2%
Source: Authors’ calculations.
From the financial projections we can conclude that both expenditures and
contributions decrease when the inflation decreases and; rise as the inflation rises. The
analytical results of the projections are presented in appendix C, tables 1-3.
4.2. Impact of changes in the percentage rate of investment
The percentage rate of investment is an important parameter which substantially affects the
responsibilities of the Public Pension Scheme.
In the basic financial assumptions, the annual long-term percentage rate of investment
is estimated to be 5.5%. Alternative rates of 4.5% and 6.5% are considered to test their impact
on the actuarial liability and the normal contribution rate as well as on the actuarial liability as
a % of GDP (table 9).
Table 9: Impact of the Percentage Rate of Investment of the Actuarial Liability and the
Normal Contribution Rate
Percentage rate of
investment:
4.5%
Percentage rate of
investment:
6.5%
Actuarial Liability 5,853,000,000 4,146,000,000
Normal Contribution Rate 48.9% 27.9%
Actuarial Liability as a % of GDP 70% 49.5%
Source: Authors’ calculations.
When the percentage rate of investment decreases by 1% the actuarial liability
increases by 20% and the normal contribution rate increases by 12.4%. However, when the
percentage rate of investment increases by 1%, then the actuarial liability decreases by 17.7%
and the normal contribution rate decreases by 8.6%. See also table 4 in Appendix C. The
projections of income and expenditures of the Scheme are not affected by the percentage rate
of investment.
4.3. Impact of changes in the mortality rate
The main assumption for the probability of mortality is based on the PA (90), decreased by
25% in the beginning. In the long-term within a time period of thirty years it is decreased by
50%. According to this assumption the life expectancy at the age of 60 is 20.5 years. If the
mortality rate is higher and the life expectancy at the age of 60 is 18 years, then the actuarial
liability and the normal contribution rate decrease. The results shown in table 10 are
comparatively lower that the ones of the current scheme shown in table 7.
Table 10: Impact of Mortality Rate on the Actuarial Liability and the Normal Contribution
Rate
Higher mortality rate
Actuarial Liability 4,463,000,000
Normal Contribution Rate 34.1%
Actuarial Liability as a % of GDP 53%
Source: Authors’ calculations.
113 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
In Appendix C, the tables 5 to 7, show the impacts of the mortality rate on the
demographic and financial projections. We may underline that the mortality rate does not
affect the number of the employed civil servants, since the ones who pass away will be
replaced by new employees. However, in the case of the retired employees and of those who
receive widow and orphan pensions, the higher mortality rate will result to a decrease in their
numbers and in the total expenditures of the Scheme since the pensions will be paid for a
shorter period of time. Indicatively, the average pay-as-you-go cost for the period 2007-2070,
decreases to 36.3%, whereas in the current Scheme, the average pay-as-you-go cost is 43.2%.
4.4. Impact of a rise in the number of the employed civil servants
The main projected outcomes are based on the assumption that the number of the civil
servants will increase by 2.5% annually and that within the next ten years, this rate will
gradually decrease to 1%. Beyond this time period, the long-term assumption is that the
number of the civil servants will increase only by 0.5% per year. The scenario that the number
of the civil servants remains fixed after the year 2025 has also been studied.
This assumption affects only the demographic and the financial projections since the
actuarial liability, refers only to the current civil servants. The analytical results of these
projections are presented in Appendix C, in tables 8 and 9.
In this scenario, the numbers of both the employed and the retired employees are
lower. However, the decrease in the number of the employed civil servants is greater and this
has a negative impact on the ratio of protection.
Also the expenditures of the scheme are lower but the long-term pay as you go cost
increases since the number of the employed civil servants who will contribute to the Scheme
is lower.
5. Alternative Reform Options
In this paragraph, we study alternative reform options that include parametric changes in the
current providences of the Scheme. The objective, is to identify the reform options that have a
positive impact on the finances of the Scheme. Specifically, we study the following scenarios:
a. A rise in the contributions of the civil servants to the Scheme;
b. Estimating the pension rise based on the inflation rate;
c. Extending the retirement age;
d. Rising the contributor factor (coefficient) of the lump sum benefit;
e. Changing the methodology in estimating the pension benefit;
f. Decreasing the contributor factor of the widow pension;
g. Decreasing the benefit for the premature retirement; and
h. Combined reform scenarios.
5.1. A rise in contributions
The contributions of the civil employees to the Scheme, cover a very small percentage of the
cost of the widow pension. In this section, we examine the total contribution of the civil
servants to the Scheme as well as their contribution to the widow pension.
5.1.1. Total contribution
The cost of benefits of the Public Pension Scheme is equal to 36.5% of the total wages paid to
the civil employees by the government of Cyprus, and this creates a substantial financial
problem.
For this reason, we are discussing three alternative scenarios: a 5%, a 7.5% and a
10% contribution of the civil employees to the Scheme. In these scenarios we assume that,
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 114
this is the total contribution of the civil servants, including the contribution for the widow
pension.
A rise in the contributions of the civil employees for financing the benefits of the
Scheme will decrease its cost as a % of the GDP. The projection of the expenditures has been
examined in connection with the projection of the GDP. The results of these projections are
given in table 11 and in appendix D, table 10. It is clear, that even with a 10% contribution,
the total cost cannot be completely covered.
Table 11: Cost of the Scheme as a % to GDP, in real prices of 2007
2007 2008 2009 2010 2020 2030 2040 2050 2060
Without
Contribution 2.1% 2.1% 2.2% 2.2% 2.1% 2.2% 2.8% 2.8% 2.9%
5%
Contribution 1.7% 1.7% 1.8% 1.9% 1.8% 1.9% 2.5% 2.6% 2.7%
7.5%
Contribution 1.6% 1.6% 1.7% 1.7% 1.7% 1.8% 2.4% 2.5% 2.5%
10%
Contribution 1.4% 1.4% 1.5% 1.5% 1.5% 1.6% 2.3% 2.3% 2.4%
Source: Authors’ calculations
As a conclusion, the long term cost of expenditure in relationship to GDP decreases to
2.4% if the civil employees contribute the 10% of their salaries.
5.1.2. Contribution for covering the cost of the widow pension
In this section we are examining the contributions of the civil employees for covering the
widow pension.
Up to a ceiling fixed by the General Social Security System (GSSS), the civil
employees contribute the 0.75% of their annual remunerations. For remunerations above this
ceiling, the civil employees contribute the 1.75% of their annual remunerations. The objective
of this contribution is to finance part of the widow pension.
The mean of the pay as you go cost of the Scheme for the period 2007-2070 is
currently 43.2% (table 7). The cost for the widow pensions is 7%. Even with contributions of
7%, only up to 2037, the contributions will be adequate to cover the total cost of the widow
pensions (Appendix D, table 11). After 2037 the contributions must rise to 10%.
In 2007, the contributions covered only the 30% of the annual expenditure of the
Scheme. In the long-term the contributions will cover only the 10%. For covering the total
expenditure of the Scheme, the contribution should have been 7%. 3.5% to be paid by the
civil employees and 3.5% by the government.
In Appendix D, tables 10 and 11, the projections of the contributions of, 5%, 7%,
7.5% and 10% are presented as well as the projections for the total expenditures and the
expenditure for the widow pension.
5.2. Estimating the pension rise based only on the inflation rate.
Currently, pension rises, are estimated based on the inflation rate and the general salary rises
of the incumbent civil employees. Due to the fact that the general salary rises are granted to
the incumbent civil employees based on their productivity, it is not logical to grant it to the
retirees as well.
In this paragraph we examine the scenario that pensions are readjusted on the basis
of the inflation rate only. That is by 2% annually and not by 3.5% as it is currently the case.
115 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table: 12: Impact of 2% Pension Rise on the Actuarial Liability and the Normal Contribution
Rate
Readjustment of Pensions by 2%
Actuarial Liability 4,011,000,000
Normal Contribution Rate 29.3%
Actuarial Liability as a % of GDP 47.8%
Source: Authors’ calculations.
Comparing the actuarial liability and the normal contribution rate as at 31/12/2006
(see table 7), to the ones when pensions rise only by 2%, we observe a decrease of 21.7 % in
the actuarial liability and a decrease of 7.2% in the normal contribution rate. In Appendix D
(tables 12 and 13), the impact of the new pension readjustment of 2% on the financial
projections, is shown as well. The expenditures are lower and the average pay as you go cost
for the period 2007-2070, is only 37% in comparison to 43.2% in the current Scheme.
5.3.Extending the retirement age
In this paragraph we discuss the impact of extending the retirement age on the actuarial
liability and on the normal contribution rate. Specifically, we examine the case of extending
the retirement age of the public educators to the age of 63. In the case of the military surgeons
and the policemen, for those who currently retire at the age of 55, we examine the case of
extending their retirement at the age of 60. For those who currently retire at the age of 60, we
examine the case of extending their retirement at the age of 63.
Examining this scenario is necessary, due to the recent extension of the retirement
age of the civil employees to 63, as well as due to the demographic changes in Cyprus.
As a consequence of extending the retirement age, there will be an increase in the
number of contributing years (positive impact), an increase in the benefits paid (negative
impact) and fewer years for paying the benefit (positive impact).
If we compare the results of table 7 with those of table 13, we can see that the
actuarial liability decreases by 7.4% and the normal contribution rate by 4.2%.
Table 13: Impact of Extending the Retirement Age on the actuarial Liability and the Normal
Contribution Rate
Extending the Retirement Age to the
60th and the 63rd Year of Age
Actuarial Liability 4,546,000,000
Normal Contribution Rate 32.3%
Actuarial Liability as a % of GDP 54.3%
Source: Authors’ calculations
Comparing the financial projections presented in Appendix D, table 16 with the
results in table 5, we observe a decrease in the expenditures and this is due to the shorter time
period during which the benefit is paid. Although the benefit paid is greater due to the
extended years of service and the higher salaries received, the period during which the benefit
is paid is substantially lower. Specifically, in this scenario the average retirement age
increases by two years.
The results of the demographic projections are presented in Appendix D, table 15. If
we compare the results of the current scheme presented in table 4 with the results of this
scenario presented in table 15, Appendix D, we see that the number of the retirees in the
projected years is substantially lower and the ratio of protection is higher.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 116
5.4. Impact of rising the contributor factor (coefficient) of the lump sum benefit
To an employee who has completed 400 months of service to the public sector (full service),
the pension currently paid by the Scheme is equal to 50% of the employee’s last monthly
salary. In the past the pension paid was 2/3 (66.66%) of the employee’s last monthly salary.
However, it was agreed to decrease it to 50% of the last monthly salary and the remainder of
the sum to be paid as a lump sum. Therefore, in order to convert this sum into a lump sum it
was necessary to take into consideration the life expectancy rate at the retirement age; being at
the age of 60. Based on the life expectancy rate, this lump sum was fixed at 12.5/3 of the
pension. In 1988 it was revised at 14/3 of the pension and since then, it remains fixed. Today,
for all employees whose retirement age has been extended to the 63rd year of age, the
coefficient of the lump sum increases by ½ a unit for every 12 months of service beyond the
400 months, with a maximum coefficient of 15/3.
Based on data from the statistical service of the Republic of Cyprus, the average life
expectancy for both men and women at the age of 60 is around 22.5 years. Although the age
of retirement for the majority of the civil employees is the age of 63, we shall examine the
level of the coefficient at the age of 60, so that to take also into consideration the members of
the scheme who retire earlier.
According to the current life expectancy, the assumption for the percentage rate of
investment and the assumption for the estimated rise in pensions, the lump sum coefficient is
estimated to be 17.5/3. If we consider that the retirement age, is the age of 63, then the
coefficient amounts to 16.3/3. In this section we examine two scenarios: in the first scenario,
the coefficient is 16.3/3 and in the second scenario is 17.5/3. Their impact on the actuarial
liability and on the normal contribution rate, is presented in table 14.
Table 14: Impact of Changing the Lump Sum Coefficient, on the Actuarial Liability and on
the Normal Contribution Rate
Lump Sum Coefficient =
16.3/3
Lump Sum Coefficient =
17.5/3
Actuarial Liability 4,983,000,000 5,043,000,000
Normal Contribution Rate 37.9% 38.7%
Actuarial Liability as a %
of GDP 59.5% 60.2%
Source: Authors’ calculations
In comparison to the current Scheme (table 7), the actuarial liability increases by 2%
in the first scenario and by 3.3% in the second scenario. The normal contribution rate
increases by 1.4% and by 2.2% respectively. In Appendix D, tables 18 and 19, the impact of
the alternative lump-sum coefficients on the financial projections are presented. The average
pay-as-you-go cost for the period 2007-2070 increases to 44.7% and 45.5% respectively for
both scenarios in comparison to 43.2% (table 6) which is currently the average pay as you
cost of the Scheme.
5.5. Changing the methodology in estimating the pension benefit
According to the current regulations, the pension benefit is estimated based on the last salary
before retirement. In this scenario, we examine the case that the pension benefit is estimated
based on the average salary of the last two years of employee’s service, before retirement.
117 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table 15: Impact of Estimating the Pension Benefit, based on the average salary of the last
two years of Service, on the Actuarial Liability and the on the Normal Contribution Rate
Pension Benefit Based on the
Average Salary of the Last Two
Years of Employment
Actuarial Liability 4,813,000,000
Normal Contribution Rate 35.8%
Actuarial Liability as a % of GDP 57.4%
Source: Authors’ calculations
Comparing tables 7 and 15, we see that when the new methodology for estimating
the pension benefit is applied, the actuarial liability and the normal contribution rate decrease
by 1.5% and 0.7% respectively. In the Appendix D, the tables 20 and 21, show the impact of
the new methodology for estimating the pension benefit, on the financial projections. The
average pay-as-you-go cost for the period 2007-2070 is 42% in comparison to the current
Scheme which is 43.2%.
5.6. Decreasing the contributor factor (coefficient) of the widow pension
In 1988 the contributor factor for estimating the widow pension increased from 50% to 75%
of the pension benefit that should had been received by the passed away civil employee.
In this section, we examine the scenario of decreasing the contributor factor to 60%.
The 60% is chosen to be more acceptable in comparison to the 50%, because the 60% is the
contributor factor for the widow pension used by the General Social Insurance Fund.
Table 16: Impact of Decreasing the Contributor Factor of the Widow Pension, on the
Actuarial Liability and on the Normal Contribution Rate
Widow Pension: 60% of
the retirement pension
Actuarial Liability 4,774,000,000
Normal Contribution Rate 35.2%
Actuarial Liability as a % of GDP 57%
Source: Authors’ calculations
Comparing the data in table 16 with that of table 7, it can be seen that the actuarial
liability decreases by 2.3% and the normal contribution rate by 1.3%. The projections for the
expenditures are presented in the Appendix D, table 23. The average pay-you-go-cost for the
period 2007-2070 is 41.9% in comparison to 43.2% in the current Scheme. The pay as you go
cost for the widow pension only, decreases to 5.7% from 7% in the current Scheme.
Therefore, if the contribution of the civil employees is revised, in case of full financing by the
civil employees, their contribution will be 5.7%. In case that the cost of financing will be
equally shared between the civil employees and the government then their contribution will be
2.8%.
5.7. An actuarial decrease of the premature (early) retirement pension benefit
According to the revised law of 2005, eligible to premature retirement are only the civil
employees who have completed five years of service and are not younger than 48. To the
employees who apply for premature retirement, a lump sum benefit is paid but the pension
benefit is not paid until the retiree reaches the age of 58. As from the date of the premature
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 118
retirement until the date that the pension benefit will be paid to the retiree, the pension benefit
rises annually by the same percentage by which the public pensions rise.
Employees employed before 2005, can apply for a premature retirement at the age of
45 but the pension benefit will be paid at the age of 55.
In both cases, the premature pension benefit does not actuarially decrease and does
not take into account the longer period of time during which the retired employee will receive
the pension benefit. In this section, we estimate the actuarial decrease of the premature
pension benefit, so that, the present value of the total pension benefits that the retired
employee will receive, to be equal to the value of the pension benefits that would have been
received in case of normal retirement (table 17). On average, for each year before normal
retirement, the premature pension benefit decreases by 5%.
Table 17: Actuarial Decrease of the Pension Benefit for Premature Retirement
Retirement Age Actuarial Decrease
55 24%
56 23%
57 21%
58 19%
59 17%
60 15%
61 10%
62 5%
Source: Authors’ calculations
5.8. Combined reform scenarios
In this section, the impact of a combination of alternative scenarios discussed above is
examined. Specifically, we are examining a scenario which takes into account the following
changes:
Pensions rise based on the inflation rate.
The extension of the retirement age to 63 for those employed in the public
education and to 60 for those employed in the police and the army.
Increasing the lump sum benefit to 16.3/3 of the pension benefit.
Decreasing the widow pension to 60% of the pension benefit.
The pension benefit is estimated based on the average salary of the employee in the
last two years of service before retirement.
Table 18: Impact of a Combined Scenario on the Actuarial Liability and the Normal
Contribution Rate
Impact of a
Combined
Scenario
Actuarial Liability 3,682,000,000
Normal Contribution Rate 26.1%
Actuarial Liability as a % of GDP 44%
Source: Authors’ calculations
In this combined scenario, comparing the data of tables 7 and 18, the actuarial liability
decreases by 32.6% and the normal contribution rate by 10.4%.
Concerning the financial projections (Appendix D, table 25), it is worthy to note that, the
long-term expenditures as a percentage of GDP decrease substantially to 2.2%. Also, the
119 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
average pay-as-you-go cost decreases to 33.1% in comparison to 43.2% in the current
scheme. This gives us an approximate decrease of 10%.
6. Conclusions and Suggestions for Further Research
In this paper, a number of alternative reform options of the public pension scheme of the
Republic of Cyprus are examined and their impact on the financial projections has been
identified. The objective is to identify the trend and the extend of the impact that these reform
options have on the financial projections and mainly on the pay as you go cost, the actuarial
liability, the normal contribution rate and the total expenditures of the Scheme.
The reform options examined and the outcomes of their implementation are:
1. An increase in the contributions of the civil employees for financing the Scheme: based on the outcomes of the study even with a 10% contribution the total cost of
expenditure cannot be covered. However, this contribution decreases the expenditures as a
% of GDP to 2.4%.
2. A rise in the contribution of the widow pension: with a 7% contribution, the cost of
widow pension can be covered only up to 2037.
3. The pension rise is estimated based on a 2% inflation rate: In this case, the actuarial
liability decreases by 21.7% and the normal contribution rate decreases by 7.2%.
4. The retirement age is extended to 63 for the public academics and to 60 and 63 for
those employed in the army and the police respectively: the study reveals that the
actuarial liability decreases by 7.4% and the normal contribution rate by 4.2%.
5. Rising the contributor factor (coefficient) of the lump-sum benefit: two scenarios are
examined; 16.3/3 and 17.5/3 of the pension. In both scenarios the normal contribution rate
increases by 1.4% and 2.2% respectively and the actuarial liability increases by 2% and
3.3% respectively. The average pay-as-you-go cost increases to 44.7% and to 45.5%
respectively.
6. The pension benefit is estimated based on the average salary received in the last two
years of the employees’ service: the actuarial liability decreases by 1.5% and the normal
contribution rate by 0.7%. The average pay-as-you-go cost for the period 2007-2070,
decreases from 43.2% to 42%.
7. Decreasing the contributor factor (coefficient) of the widow pension from 75% to
60% of the pension: as a result, the actuarial liability decreases by 2.3% and the normal
contribution rate by 1.3%. The average pay-as-you-go cost for the period 2007-2070
decreases to 41.9% from 43.2% which is currently.
8. Actuarial decrease of the pension benefit for early retirement: on average, for each
year before normal retirement, the pension benefit decreases by 5%.
9. Combined reform scenario: based on this scenario, the actuarial liability decreases by
32.6% and the normal contribution rate decreases by 10.4%. In the long-term the
expenditures decrease to 2.2% of GDP. Also, the average pay-as-you-go cost decreases to
33.1% from 43.2% which is now (e.g., the period the research was carried out).
In table 19 the financial impacts of the alternative reform options studied are pointed out.
It can be seen that the greatest positive impacts have, (a) the extension of the retirement age;
(b) the pension rise to be estimated based on the inflation rate; (c) decreasing the widow
pension to 60% of the pension; and (d) estimating the pension benefit based on the average
salary of the employee in the last two years of service before retirement. Of course any rise in
the contributions of the employees such as a rise in total contributions to 10% will positively
affect the financial balances of the Scheme.
Changes on the above mentioned areas, will lead to a decrease in the annual
expenditures of the Scheme which will make it sustainable in the long-term. Moreover, they
will assist in decreasing the gap between the benefits offered by the Social Insurance System
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 120
to the employees in the private sector and the benefits that the Public Pension Scheme offers
to the retired civil servants.
Table 19: Impacts of Alternative Reform Options
Financial Impacts
Reform Options Actuarial
liability
Long-term Total
Expenditures as a
% of GDP in
Prices of 2007
Normal
contribution
rate
Average Pay as you
go cost for the
period
2007-2070
1. Pension rise of 2%,
based on the inflation
rate
21.7%
decrease
0.5% decrease 7.2%
decrease
6.2% decrease
2. Extending the
retirement age
7.4%
decrease
0.2% decrease 4.2%
decrease
3.3% decrease
3. Rising the
contributor factor of
the lump sum to
16.3/3 and 17.5/3 of
the pension
2% and 3.3%
increase
3% and 3.1%
increase
1.4% and
2.2%
increase
1.5% and 2.3%
increase
5. Decreasing the
contributor factor of
the widow pension to
60% of the retirement
pension
2.3%
decrease
0.1% decrease 1.3%
decrease
1.3% decrease
6. Combined reform
scenarios:
* Rising the
retirement age
(positive impact).
* Increasing the lump
sum benefit to 16.3/3
of the pension
(negative impact).
* Decreasing the
widow pension to
60% of the pension
(positive impact).
* The pension benefit
is estimated based on
the average salary of
the employee in the
last two years of
service before
retirement (positive
impact).
32.6%
decrease
0.5% decrease 10.4%
decrease
10.1% decrease
Based on- this study, a more complete suggestion for reforming the public pension
scheme of the Republic of Cyprus can include not only parametric changes but also structural
changes. A trend which is worthwhile to mention and it can be an issue for further research as
well, is the complete elimination of the public pension scheme of the civil servants and the
121 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
development of one pension fund for all the employees of the Republic of Cyprus, both in the
public and in the private sector. Robert Palacios and Edward Whitehouse (2006) have
compared schemes within the same country covering private sector workers as well. They
also reviewed key policy issues related to pension schemes covering civil servants and other
public sector workers. In particular, they have identified that, there is little justification for
maintaining parallel schemes in the long run.
This paper which is the outcome of the undertaken funded research, contributes to
the academic society as well as to the community of the Republic of Cyprus, in a way that the
presented outcomes of the research project, may enable the decision-makers responsible for
determining public policies as well as the social partners, to have a better picture of the
impacts of the alternative reform options on the finances of the Public Pension Scheme of the
Republic of Cyprus. This may lead to a productive dialogue between the Government and the
interested social partners, in an effort to design and implement an efficient and operationally
applicable programme for reforming the Public Pension Scheme of the Republic of Cyprus.
Definitely an economically sustainable Public Pension Scheme will benefit the society of
Cyprus.
The results of the research project have been utilized by the government of the
Republic of Cyprus at its negotiations with troika during the period of the economic recession
of 2013. Still the results can be of benefit to the social partners in their further discussions
with the government of The Republic of Cyprus, for further developing the pension system of
the civil employees.
Notes
1. The exchange rate of the Cyprus Pound (£) = € 0.585274. All the monetary values given
in the tables of this paper are in Cyprus Pounds (₤). This is because the currency of the
Republic of Cyprus during the period when the research project was carried out was the
Cyprus Pound (₤). Cyprus entered the Euro Currency Area in January 2008.
7. References
American Academy of Actuaries (2004). Fundamentals of current pension funding and
accounting for private sector pension plans, an analysis of the pension committee of
the American academy of actuaries.
Barr, N. (2000). Reforming Pensions: Myths, Truths, and Policy Choices. IMF Working
Paper, Fiscal Affairs Department, 2000.
Barr, N. and Diamond, P. (2009). Pension Reform. A Short Guide, Oxford University Press.
Capretta, J.C. (2007). Global ageing and the sustainability of public pension systems, a report
of the ageing vulnerability index project, Center for Strategic and International
Studies, Washington, 2007.
Central Bank of Cyprus (2006). Annual Economic Indicators.
Cichon Michael (1999). National Defined – Contribution Schemes: Old Wine in New Bottles.
International Social Security Review, 52(4), pp. 87 – 105.
Cogan, J. and Mitchell, O. (2002). The Role of Social Security in Household Decisions: VAR
Estimates of Saving and Fertility Behaviour in Germany. Econometric Society
Conference.
Diamond, P. (2002). Social Security Reform, Oxford University Press.
European Commission. (2008). The 2009 Ageing Report Underlying Assumptions and
Projected Methodologies for the EU 27 Member States 2007 – 2060, Economic and
Financial Affairs, Directorate – General, European Economy 7, 2008.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 122
European Commission (2010). Joint Report on Pensions Progress and key challenges in the
delivery of adequate and sustainable pensions in Europe. Directorate-General for
Economic and Financial Affairs.
European Commission, Economic and Financial Affairs, (2017).
Eurostat (2015). Social Protection Statistics.
Louca, Ch., Korres, G., Tsobanoglou, G. and Kokkinou, A. (2011). Assessing the public
pension scheme of the Republic of Cyprus. Pensions, 16(3), pp. 151-167.
Matt Smith. Projected Unit Credit. Office of the State Actuary, presentation (2005).
Ministry of Finance. Demographic and Financial Assumptions, Nicosia (2006).
Ministry of Finance. Annual Report, Nicosia (2008).
Palacios, R. and Whitehouse, E.R. (2006). Civil-service pension schemes around the world.
The World Bank, Social Protection Discussion Paper 0602, Washington, 2006.
Republic of Cyprus, Pension Law of 1997 (N. 97(I)/97) (as it was revised by Law 3(I)/98),
Republic of Cyprus Gazette, 3207, Nicosia (1997).
123 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
APPENDIX A:
Table 1: Members of the Public Pension Scheme of the Civil Servants of the Republic of
Cyprus by Age Distribution as in 2006 Men Women
Age
Distribution
Total Number
of Members in
the Scheme
Average
Period of
Service
Average
Monthly
Salary
Total Number
of Members in
the Scheme
Average
Period of
Service
Average
Monthly
Salary
<20 4 0.6 785 2 0.1 635
20-25 540 2.0 794 179 1.7 680
25-30 1,867 4.7 870 2,095 2.8 945
30-35 2,408 8.0 1,060 2,688 6.5 1,150
35-40 1,897 10.8 1,319 2,200 9.5 1,261
40-45 1,543 13.4 1,543 2,016 10.8 1,433
45-50 2,281 18.3 1,737 2,240 13.6 1,671
50-55 2,348 22.2 1,915 2,387 17.1 1,908
55-60 2,278 26.0 2,211 1,558 19.5 2,096
60-65 292 30.7 2,455 118 19.8 2,262
65+ 2 34.7 5,279 0 0.0 0
Total 15,460 15.1 1,534 15,483 11 1,465
Table 2: Retired Employees y Age Distribution as in 2006
Men Women
Age
Number of
Retired
Employees
Average
Monthly Pension
Number of
Retired
Employees
Average Monthly
Pension
30-35 4 428 0 0
35-40 1 743 2 201
40-45 6 148 2 314
45-50 50 1,007 10 400
50-55 198 919 38 436
55-60 939 813 358 841
60-65 2,693 882 1,118 899
65-70 2,377 762 747 722
70-75 1,402 821 373 775
75-80 762 818 192 804
80-85 407 782 62 660
85-90 182 713 24 770
90-95 53 639 20 655
95-100 16 706 2 412
>100 6 385 6 479
Total 9,096 820 2,954 808
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 124
Table 3: Receivers of Widow/Orphan Pension by Age Distribution as in AS IN 2006
Age Number of
Widows/Orphans
Average Monthly
Pension
<35 15 264
35-40 14 319
40-45 20 195
45-50 40 197
50-55 89 308
55-60 174 433
60-65 256 621
65-70 297 612
70-75 417 499
75-80 347 461
80-85 325 377
85-90 188 348
90-95 109 300
95+ 30 303
Total 2,321 457
125 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
APPENDIX B:
Table 4: Mortality – PA90
Ηλικία Άνδρες Γυναίκες Ηλικία Άνδρες Γυναίκες
30 0.000584 0.000301 66 0.027296 0.013291
31 0.00057 0.000301 67 0.029778 0.014797
32 0.000613 0.000332 68 0.032479 0.016471
33 0.000666 0.000371 69 0.035416 0.018331
34 0.000725 0.000413 70 0.038608 0.020396
35 0.000791 0.000461 71 0.042075 0.022689
36 0.000864 0.000514 72 0.045838 0.025233
37 0.000947 0.000573 73 0.04992 0.028053
38 0.001041 0.000639 74 0.054346 0.031179
39 0.001149 0.000712 75 0.059139 0.034641
40 0.001274 0.000794 76 0.064326 0.038472
41 0.001419 0.000885 77 0.069935 0.042708
42 0.001589 0.000987 78 0.075992 0.047387
43 0.001788 0.0011 79 0.082528 0.052551
44 0.002022 0.001227 80 0.089572 0.058243
45 0.002298 0.001367 81 0.097153 0.06451
46 0.002623 0.001524 82 0.105301 0.0714
47 0.003006 0.001699 83 0.114047 0.078963
48 0.003456 0.001895 84 0.123418 0.087253
49 0.003984 0.002112 85 0.133444 0.096321
50 0.004601 0.002354 86 0.14415 0.106223
51 0.005318 0.002624 87 0.155561 0.117011
52 0.006147 0.002925 88 0.167699 0.128736
53 0.007099 0.003261 89 0.18058 0.141448
54 0.008184 0.003634 90 0.194221 0.155192
55 0.009412 0.004051 91 0.208629 0.170007
56 0.010789 0.004515 92 0.223809 0.185924
57 0.012321 0.005031 93 0.23976 0.202968
58 0.013517 0.005607 94 0.256471 0.22115
59 0.014765 0.006247 95 0.273928 0.240469
60 0.016127 0.006961 96 0.292106 0.26091
61 0.017612 0.007755 97 0.310973 0.282443
62 0.019232 0.00864 98 0.330491 0.305019
63 0.020997 0.009624 99 0.350609 0.328574
64 0.02292 0.010719 100 0.371274 0.353024
65 0.025015 0.011937 101 1 1
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 126
APPENDIX C: Analytical Results of the Simulation Scenarios
1. Impact of inflation
Table: 1: Actuarial liability and normal contribution rate
Actuarial Liability Inflation rate: 1% Inflation rate: 3%
Active civil employees 2,402,000,000 3,958,000,000
Retired Employees 1,509,000,000 1,834,000,000
Beneficiaries of widow pension 149,000,000 179,000,000
Total Actuarial Liability 4,060,000,000 5,971,000,000
Normal contribution rate 27.6% 49.1%
Table 2: Expenditures and contributions (₤ mil.) with 1% inflation rate
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Πληθωρισμός 1%
Total
expenditur
es
186.
1
198.
9
220.
8
233.
5
302.
2
369.
9
580.
6
1,027.
4
1,415.
6
1,944.
0
2,706.
2
Contributi
ons 4.9 5.3 5.6 5.8 7.2 8.9 13.3 15.3 19.3 26.5 35.7
Pay as you
go cots
28.4
%
28.5
%
30.1
%
30.7
%
32.6
%
32.6
%
35.3
%
51.4
%
54.3
%
54.3
%
56.0
%
Expenditur
es as a %
of GDP in
prices of
2007
2.0% 2.1% 2.2% 2.3% 2.2% 2.1% 2.2% 2.8% 2.9% 3% -
Table 3: Expenditures and contributions (₤ mil.) with 3% inflation rate
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Inflation rate: 3%
Total
expenditur
es
188.
7
204.
6
230.
6
248.
4
349.
8
464.
5
857.
8
1,821.
8
2,987.
7
4,912.
6
8,287.
5
Contributi
ons 4.9 5.3 5.7 6.1 8.3 11.4 20.7 28.7 43.7 72.4 118.5
Pay as you
go cots
28.8
%
29.1
%
30.7
%
31.1
%
32.6
%
32.1
%
33.7
%
48.6
%
50.4
%
49.7
%
51.3
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.1% 2.2% 2.2% 2.2% 2% 2.1% 2.6% 2.6% 2.7% -
2. Impact of the percentage rate of investment
Table 4: Actuarial liability and normal contribution rate
Actuarial liability Percentage rage of
investment: 4.5%
Percentage rate of
investment: 6.5%
Active civil employees 3,842,000,000 2,484,000,000
Retired employees 1,833,000,000 1,513,000,000
Beneficiaries of widow pension 178,000,000 149,000,000
Total Actuarial Liability 5,853,000,000 4,146,000,000
Normal contribution rate 48.9% 27.9%
127 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
3. Impact of mortality
Table 5: Actuarial liability and normal contribution rate
Actuarial liability Higher mortality rate
Active civil employees 2,857,000,000
Retired employees 1,464,000,000
Beneficiaries of widow pension 142,000,000
Total Actuarial Liability 4,463,000,000
Normal contribution rate 34.1%
Table 6: Demographic projections
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Active
civil
employees
31,72
0
32,50
4
33,12
2
33,73
5
35,89
0
37,72
2
40,87
8
43,00
0
45,24
4
47,62
3
50,06
5
Retired
employees
12,34
6
12,65
8
13,09
1
13,50
8
15,24
1
15,98
1
16,55
9
20,85
1
24,29
2
25,87
3
27,51
0
Beneficiari
es of
widow
pension
2,485 2,650 2,811 2,971 3,784 4,570 5,765 6,374 7,034 8,042 8,715
Ratio of
Protection 2.1 2.1 2.1 2.0 1.9 1.8 1.8 1.6 1.4 1.4 1.4
Table 7: Expenditures and contributions (₤ million)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
e
186.
8
200.
9
224.
8
239.
7
319.
5
401.
9
674.
2
1,319.
6
1,977.
9
2,906.
4
4,353.
7
Contributi
ons 4.9 5.4 5.8 6.2 8.1 10.6 17.4 21.8 30.1 45.3 67.3
Pay as you
go cost
28.6
%
28.3
%
29.6
%
29.8
%
31.0
%
30.4
%
32.0
%
46.7
%
48.6
%
47.2
%
47.6
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.0% 2.1% 2.2% 2.2% 2% 2.1% 2.6% 2.6% 2.6% -
4. Projections of retired and active employees
Table 8: Demographic projections
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Active civil
employees 31,752 32,503 33,123 33,735 36,138 37,772 38,244 38,248 38,248 38,249 38,250
Retired
employees 12,465 12,895 13,448 13,990 16,370 17,736 19,280 24,126 27,753 28,621 29,111
Beneficiaries
of widow
pension
2,443 2,571 2,698 2,826 3,507 4,228 5,535 6,329 6,819 7,516 8,165
Ratio of
Protection 2.1 2.1 2.1 2.0 1.8 1.7 1.5 1.3 1.1 1.1 1.0
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 128
Table 9: Expenditures and contributions (₤ million)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
es
187.
4
202.
4
227.
5
243.
7
331.
6
425.
8
733.
8
1,426.
3
2,114.
2
2,968.
4
4,380.
0
Contributi
ons 4.9 5.4 5.8 6.3 8.2 10.6 16.9 20.1 25.8 37.1 52.7
Pay as you
go cost
28.6
%
28.5
%
29.9
%
30.2
%
32.0
%
32.0
%
36.1
%
55.3
%
61.0
%
59.0
%
61.3
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.1% 2.2% 2.2% 2.2% 2.1% 2.2% 2.8% 2.8% 2.7% -
129 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
APPENDIX D: Analytical Results of alternative reform scenarios 1. Rise in contributions
Table 10: Total expenditures and employees’ contributions of 5%, 7.5% and 10% (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060
Total
expenditures
187.
4
202.
4
227.
5
243.
7 331.6 425.8 733.6
1,429.
8
2,150.
4
3,220.
3
Contribution
s 5%
31.1
5
34.1
4
36.7
8
39.1
8 50.41 64.75
103.9
0 139.78 199.91 302.41
Contribution
s 7.5%
43.6
1
47.7
9
51.5
0
54.8
5 70.58 90.65
145.4
6 195.69 279.88 423.37
Contribution
s 10%
62.2
9
68.2
8
73.5
6
78.3
6
100.8
2
129.5
1
207.8
0 279.56 399.82 604.82
Table 11: Expenditures and contributions for widow pensions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060
Expenditures
for widow
pension
16.4 19.2 22.2 25.3 44.5 68.7 125.8 200.1 338.0 597.5
Current
contributions 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4
Contributions
7% 44.1 47.8 51.5 54.8 70.6 90.7 145.5 195.7 279.9 423.4
2. Revising the method of readjusting of pensions
Table 12: Actuarial liability and normal contribution rate
Actuarial liability Readjustment of Pensions by 2%
Active civil employees 2,495,000,000
Retired employees 1,378,000,000
Beneficiaries of widow pension 138,000,000
Total Actuarial Liability 4,011,000,000
Normal contribution rate 29.3%
Table 13: Expenditures and contributions after readjusting pensions by 2% (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
es
185.
3
198.
1
220.
7
234.
3
305.
9
378.
8
633.
1
1,241.
7
1,802.
0
2,619.
9
3,998.
3
Contributi
ons 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Pay as you
go cost
28.3
%
27.9
%
29.0
%
29.0
%
29.6
%
28.5
%
29.9
%
43.8
%
44.2
%
42.4
%
43.6
%
Expenditur
es as a %
of GDP in
prices of
2007
2.0
%
2.0
%
2.1
%
2.1
% 2.1% 1.9% 1.9% 2.4% 2.4% 2.4% -
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 130
3. Extension of the retirement age
Table 14: Actuarial liability and normal contribution rate
Actuarial liability
Retirement at the Age of 63
for the academia and 60 for the
police and the army
Active civil employees 2,724,000,000
Retired employees 1,659,000,000
Beneficiaries of widow pension 163,000,000
Total Actuarial Liability 4,546,000,000
Normal contribution rate 32.3%
Table 15: Retirement age – demographic projections
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Active
civil
employees
31,75
2
32,50
3
33,12
3
33,73
5
35,89
3
37,72
5
40,87
5
42,99
7
45,24
6
47,62
3
50,06
3
Retired
employees
12,46
5
12,89
5
13,44
8
13,99
0
15,32
0
16,12
2
17,02
3
21,18
7
24,83
9
26,65
3
28,16
2
Beneficiari
es of
widow
pension
2,443 2,571 2,698 2,826 3,506 4,225 5,523 6,300 6,767 7,479 8,261
Ratio of
Protection 2.1 2.1 2.1 2.0 1.9 1.9 1.8 1.6 1.4 1.4 1.4
Table 16: Extending the retirement age – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
es
187.
4
202.
4
227.
5
243.
7
290.
9
391.
4
644.
0
1,346.
3
1,992.
9
2,964.
0
4,421.
1
Contributi
ons 4.9 5.4 5.8 6.3 8.4 11.2 18.7 23.5 31.2 47.0 70.2
Pay as you
go cost
28.6
%
28.5
%
29.9
%
30.2
%
27.4
%
28.4
%
29.0
%
45.4
%
47.5
%
46.6
%
46.4
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.1% 2.2% 2.2% 2% 2% 2% 2.6% 2.6% 2.7% -
4. A change in the contribution factor of the lump sum benefit
Table 17: Actuarial liability and normal contribution benefit
Actuarial liability Lump-sum benefit =
16.3/3
Lump-sum benefit = 17.5/3
Active civil employees 3,161,000,000 3,221,000,000
Retired employees 1,659,000,000 1,659,000,000
Beneficiaries of widow pension 163,000,000 163,000,000
Total Actuarial Liability 4,983,000,000 5,043,000,000
Normal contribution rate 37.9% 38.7%
131 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Table 18: Lump sum benefit (16.3/3) – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditures 194.2 210.0 237.2 254.0 344.2 441.1 765.4 1,489.0 2,217.0 3,314.5 5,074.2
Contributions 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Pay as you go
cost 29.7% 29.5% 31.2% 31.5% 33.3% 33.2% 36.2% 52.5% 54.4% 53.7% 55.3%
Expenditures
as a % of
GDP in prices
of 2007
2.1% 2.1% 2.3% 2.3% 2.3% 2.2% 2.3% 2.9% 2.9% 3% -
Table 19: Lump-sum benefit (17.5/3) – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditures 197.7 213.9 242.3 259.4 350.7 449.1 782.0 1,519.9 2,251.7 3,363.6 5,156.9
Contributions 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Pay as you go
cost 30.2% 30.1% 31.9% 32.2% 34.0% 33.8% 36.9% 53.6% 55.2% 54.5% 56.2%
Expenditures
as a % of
GDP in prices
of 2007
2.2% 2.2% 2.3% 2.3% 2.4% 2.2% 2.4% 3% 3% 3.1% -
5. A change in estimating the pension benefit
Table 20: Actuarial liability and normal contribution rate
Actuarial liability
Estimated pension received based on the
average salary of the last two years of
service
Active civil employees 2,991,000,000
Retired employees 1,659,000,000
Beneficiaries of widow pension 163,000,000
Total Actuarial Liability 4,813,000,000
Normal contribution rate 35.8%
Table 21: Retirement pension – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditures 187.1 201.7 226.3 242.1 327.6 418.5 715.7 1,388.3 2,078.2 3,109.7 4,751.1
Contributions 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Pay as you go
cost 28.6% 28.4% 29.8% 30.0% 31.7% 31.5% 33.8% 48.9% 51.0% 50.4% 51.8%
Expenditures
as a % of
GDP in prices
of 2007
2.1% 2.0% 2.2% 2.2% 2.2% 2.1% 2.2% 2.7% 2.7% 2.8% -
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 132
6. A change in the contribution factor of the widow pension
Table 22: Actuarial liability and normal contribution rate
Actuarial liability Widow pension – 60%
Active civil employees 2,952,000,000
Retired employees 1,659,000,000
Beneficiaries of widow pension 163,000,000
Total Actuarial Liability 4,774,000,000
Normal contribution rate 35.2%
Table 23: Widow-pension – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
es
186.
9
201.
3
225.
8
241.
3
325.
3
414.
3
709.
8
1,390.
5
2,083.
0
3,100.
9
4,726.
1
Contributi
ons 4.9 5.4 5.8 6.3 8.1 10.6 17.5 21.9 30.2 45.4 67.5
Pay as you
go cost
28.6
%
28.3
%
29.7
%
29.9
%
31.5
%
31.2
%
33.5
%
49.0
%
51.1
%
50.2
%
51.5
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.0% 2.2% 2.2% 2.2% 2.1% 2.2% 2.7% 2.8% 2.8% -
7. A combination of reform scenarios
Table 24: Actuarial liability and normal contribution rate
Actuarial liability Combined reform scenario
Active civil employees 2,166,000,000
Retired employees 1,378,000,000
Beneficiaries of widow pension 138,000,000
Total Actuarial Liability 3,682,000,000
Normal contribution rate 26.1%
Table 25: Combined reform scenarios – expenditures and contributions (₤ millions)
2007 2008 2009 2010 2015 2020 2030 2040 2050 2060 2070
Total
expenditur
es
191.
2
203.
8
227.
6
240.
8
265.
3
348.
0
554.
2
1,198.
7
1,670.
0
2,398.
0
3,586.
5
Contributi
ons 4.9 5.4 5.8 6.3 8.4 11.2 18.7 23.5 31.2 47.0 70.2
Pay as you
go cost
29.2
%
28.7
%
29.9
%
29.8
%
25.0
%
25.2
%
25.0
%
40.4
%
39.8
%
37.7
%
37.6
%
Expenditur
es as a %
of GDP in
prices of
2007
2.1% 2.1% 2.2% 2.2% 1.8% 1.7% 1.7% 2.4% 2.2% 2.2%
133 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
The Royal City Andrapolis of «The Acts of Thomas»
Abstract:
In the Acts of the apostle Thomas it is mentioned that Thomas sailed to the royal city of
Andrapolis. Andrapolis should not be identified with any of the cities of India (Βarygaza or
any other city of western India) nor with the island of Socotra, but with the harbor Μηδέκιον
ἄντρον in the strait of Deire, today Bab el Mandeb of the peninsula of Arabia. Thomas arrived
in India by ship, after leaving Andrapolis.
Key words: Thomas, Andrapolis, Homerites, India, Medekion Antron
Alex Kordosis1
1 Corresponding-Address: Alex Kordosis, Degree in Political Science and History, Panteion University. Msc
Political, Economic & International Relations in the Mediterranean, University of the Aegean.Phd candidate,
University of the Aegean. Email: [email protected]
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 134
1. The Royal City Andrapolis of «The Acts of Thomas»
In the Acts of the apostle Thomas (2nd or 3rd c. A.D.)2 we find the names of the apostles with
the information that the world was divided among them, in order to preach the Gospel. India
fell by lot and division to Judas Thomas, named also Twin3, but he was disinclined to accept
the mission.4 Thomas was not willing to go to India, because India was a strange and distant
country. Then, as it is said in the Acts, our Lord sold Thomas to Hâbbân (Αββάνην),5 an agent
of Gondapharos (an Indian king), who had come in Jerusalem to hire the services of a
qualified builder. So Hâbbān and Thomas boarded a ship and sailed, having favorite wind, to
the royal city Andrapolis.6 On their arrival the townspeople were found keeping the bridal of
the King’s daughter; the newcomers were invited to take part in the rejoicings, and a Hebrew
flute girl was brought on the scene. She attracted Thomas’s attention, and she discovered a
fellow patriot in him. An attendant at the feast strikes Thomas, and the apostle predicted the
man’s imminent punishment: the man, who was a cup-bearer, was to be killed by a wild
beast- a lion (?) prowling in the neighborhood- while on his way to fetch water; the
punishment was realized. Dogs tore the body to pieces, and one of them brought the right arm
which had struck the Apostle into the banquet place. All were amazed by the occurrence: the
king urged Thomas to come in to the bridal chamber and bless the new couple. The young
couple in the sequel vowed chastity; on hearing this, the king is indignant and orders Thomas
‘the sorcerer’ to be arrested». However, Thomas with Hâbbân escaped, sailing on a boat for
India.
The question we must answer concerns the identification of the royal Andrapolis.
Andrapolis is the city of Andhra. Some scholars suggest that Andrapolis was the city of the
Andhra kings, known as Satakarnis.7 Satakarnis is similar to the toponyms Sandaruk or
Sanadruk, which was the name of Andrapolis in the syrian edition of the Acts of Thomas.8
Τhis similarity led some scholars to identify Andrapolis with Barygaza (Bharuch) of India,9 a
city of the kings of Andhra. Barygaza is known from the text of “Periplus of Erythra” (1st c.
A.D.). It was a port as well as an industrial city. Barygaza imported such raw materials as
copper, tin and lead and exported silk cloth, introduced from China, cotton cloth etc.10 It was
a very significant harbor. The island of Socotra, in the Indian Ocean, east of the cape
2. Β. Ντόβας, Άγιος απόστολος Θωμάς. Η εικόνα του ως αποστόλου των Παρθών, των Ινδών και των Κινέζων,
μέσα από τη χριστιανική γραμματεία και τις τοπικές εκκλησιαστικές παραδόσεις. Διπλωματική εργασία, Ιωάννινα
2014, p. 13. 3. Acta Philippi et Acta Thomae, accedunt Acta Barnabae, ed M. Bonnet, Acta Apostolorum Apocrypha, partis
II, vol. II. Darmstadt, 1959, p. 100: «κατὰ κλῆρον οὔν ἔλαχεν ἡ Ἰνδία Ἰούδᾳ Θωμᾷ τῷ καὶ Διδύμῳ…». 4. Α. Ε. Medlycott, Apostle Thomas an Inqury with a critical analysis of the Acta Thomae, London 1905, p. 179:
«Νow the oldest record of the division of the world among the Apostles assigns Parthia to Thomas. This was
stated by Origen (a.d. 200-254) in his Commentary on Genesis, now lost, but the passage has been recovered for
us by Eusebius….in his Hist. Eccl., lib III. C 1». 5. Μedlycott, Apostle Thomas, 180: «…. It can by no means be accepted that our Lord was forced by Thomas’
conduct to sell him as a slave to Hâbbân». We must note that Gondapheros was a real king of North India
(Gudnaphar), see Nτόβας, Άγιος απόστολος Θωμάς, σ. 57-60. Some coins of this king are saved with his name
on them (ΓΟΝΔΟΦΑΡΟΣ) 6. Acta Philippi et Acta Thomae, p. 104. 7. Nτόβας, Άγιος απόστολος Θωμάς, σ. 52. 8. Μedlycott, Apostle Thomas, p.184: «The story then proceeds to what occurred on the landing at Sandaruk (or
Sanadruk), the Greek has Andrapolis instead; both Latin versions omit the name. Gutschmidt thought he found
here an allusion to the Andhra race. This race, according to Caldwell, formed the western branch of the Telegu
race, but between it and the sea lay the Konkani on the western shores of India (see the excellent map of
ancientnIndia by Reinaud, Mémoire sur l’ Inde). The change of Sandaruk into Andrapoli V, Andrapolis, comes
about by dropping the sibilant letter and adding the termination poli V». 9. J. Kurikilamkatt, First voyage of the apostle Thomas to India. Ancient Christianity in Baruch and Taxila,
Bangalore 2005, p. 40-68. Nτόβας. Άγιος απόστολος Θωμάς, σ. 52. 10. Τhe Periplus Maris Erythraei. Text with Introduction, translation, and commentary, by L. Casson, Princeton,
1914, p. 22, 76 κ.ε
135 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Guardafui, is another place identified with Andrapolis.11 Ιn early byzantine time Socotra was
named island of Dioscuridus. Their residents were Christians (Nestorians), a mixture of Arabs
and Indians and even some Greeks. The island was «barren and damp, with rivers, crocodiles,
a great many vipers, and huge lizards».12
Αs mentioned in the Acts, after the incident with the new couple, Thomas, by taking a
ship, arrived at India.13 We, therefore, must place Andrapolis outside India, as A.E. Medlycott
notes: «Βut the town referred to in the text ought not to be in India, for in two succeeding
passages we are led to know that it was later the Apostle entered ‘in the realm of India’: the
passages are at the close of this and the beginning of the next Act. The poem of Jacob of
Sarug, which, as we said, incorporates the first two Acts of the story, also supports the
interpretation that the wedding feast which comes after the landing occurred before the
Apostle had entered India, based no doubt on the Acts».14
Which was the country where apostle Thomas with Hâbbân had arrived?
The existence of the Hebrew flute girl shows that Jews lived in Andrapolis. If we bear
in mind that the usual route to India was through the Red Sea and the harbors of Aethiopia
and Yemen (Adulis, Opone, Cane etc)15 and also that a great number of Jews lived in the land
of Homerites (Himyar),16 we must search for Andrapolis in the land of Homerites, in Yemen
(ancient Felix Arabia).
In another source, the Life of Saint Gregentius, we may read that the saint arrived to
Amlem (Αxom) from Alexandria and after boarding a ship (from Adulis), he travelled the Red
Sea to Μηδέκιον ἄντρον and to the capital city of the Himyars, Taphar.17 We think that antron
is the first part of Andrapolis (Antron+πόλις=city of Antron). Where was Andrapolis situated?
G. Fiaccadori wrote about this Medekion antron:«Τhe expression Medekion includes
another Arabic designation for Bāb al-Mandab, the ancient Maddabān (Mdbᶯ in South
Arabian epigraphy), i.e. the passage between the southern end of the Red Sea towards the
Indian Ocean: Μaḍīq literally “straight, canal”, which is also found in the Arabic version of
the Martyrion of Arethas, is likely to date from before the tenth century. It renders here,
στενός τόπος (“narrow place”) of the Greek original almost contemporary to the events
in Najrān; and becomes Maḍiq in the ensuing Ethiopic translation, not later than the thirteenth
century. The original form of the name in the Bios must have been Μηδέκιον, as transmitted
by the D.F.; ἄντρον, “cave”, but also “inner chamber closet”, seems to be a gloss, albeit a
peculiar one, of Maḍīq, conveying the same meaning “place of depth, narrowness or
straightness”, i.e. στενὸς τόπος as an outlet or passage to go through. The most important
harbour in this area is Mocha/al Mukhā, the ancient Muckhawān (Mkhwᶯ) in south Arabian
Inscriptions), which provides the closest access to Taphar/Zafar and then to Ṣan‘ā’ via
Dhamār, overland.”18 Mucka or Muza was the harbor of the capital Taphar-Zaphar and
11. M.M. Ninan, «Land and Sea routes of the Early Christian Missionaries to India»: Selected works of M.M.
Ninan, vol 3, San Jose, 2011, p. 385. Nτόβας, Άγιος απόστολος Θωμάς, p. 52. 12. Τhe Periplus Maris Erythraei, p. 68, 69: «….so huge that people eat the flesh and meet down the fat to use in
place of oil». 13. Acta Philippi et Acta Thomae, p. 123, 124. 14. A.E. Medlycott, Apostle Thomas, p. 184. 15. The Periplus Maris Erythraei, p. 8,9-10. Plinii, Natural History, ed. Loeb, V 104. Cosmas Indicopleustes 2.54
11.17. E. Warmington, The commerce between the Roman empire and India, London 1974, p. 48, 54, 55, 138.
J.I. Miller, The spice trade of the Roman empire, 29 BC to A.D. 641, Oxford 1969, σ. 145, 207. L. Boulnois, The
Silk road, transl. in English D. Chamberlin, London 1966, p. 54. 16. M. Detoraki, Le martyre de Saint Arethas et de ses compagnons, édition critique, étude et annotation.
Traduction par J. Beaucamp, Paris, 2007, passim. 17. A. Berger, Life and works of Saint Gregentios, Archbishop of Taphar, with a contribution by G. Fiaccadori,
Berlin-N. York 2006, p. 392. 18. G. Fiaccadori, «Gregentios in the land of the Hamerites». Ιn: Βerger, Life and works of Saint Gregentios, p.
50-51.
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 136
consequently the royal port. This is the reason that the “Acts of Thomas” name Andrapolis
«royal city». We don’t know Thomas itinerary, from Jerusalem. Most probably he arrived in
Andrapolis taking a ship in the port Aelana (today Aqaba) in the Red Sea.
2. References:
Acta Philippi et Acta Thomae acedunt Acta Barnabae, ed. M. Bonnet: Αcta
Apostolorum, Apokrypha, partis II, vol. II, Darmstadt 1959.
A. Berger. Life and works of Saint Gregentios, Archbishop of Taphar, with a contribution
by G. Fiaccadori, Berlin, N. York, 2006.
L. Boulnois, The Silk road, transl. in English D. Chamberlain, London 1966.
M. Detoraki, Le martyre de Saint Arethas et de ses compagnons, édition critique, étude
et annotation : Traduction par J. Beaucamp, Paris, 2007.
G. Fiaccadori, “Gregentios in the land of the Homerites”, In: Α. Βerger, Life and works of
saint Gregentios, N. York, 2006.
J. Kurikilamkatt, First voyage of the Apostle Thomas to India. Ancient Christianity in Baruch
and Taxila, Bangalore, 2005.
A.E. Medlycott, Apostle Thomas, an inquiry with a critical analysis of the Acta Thomae,
London 1905.
J. Miller, The spice trade of the Roman empire, 29 BC. to AD 641, Oxford 1969.
M.M. Ninan “Land and sea routes of the Early Christian Missionaries to India”: Selected
works of M.M Ninan, vol. 3, San Jose, 2011.
B. Nτόβας, Άγιος Απόστολος Θωμάς. Η εικόνα του ως αποστόλου των Πάρθων, των Ινδών και
των Κινέζων, μέσα από τη χριστιανική γραμματεία και τις τοπικές εκκλησιαστικές
παραδόσεις, διπλωματική εργασία, Ιωάννινα, 2014.
(The) Periplus Maris Erythraei. Text with introduction, translation, and commentary, by L.
Casson, Princeton 1914.
E. Warmington, The commerce between the Roman empire and India, London 1974.
137 Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020
Journal of Regional Socio-Economic Issues, Vol. 10, Issue 3, September 2020 138
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