MEASURING POVERTY: A SURVEY OF CONCEPTS AND METHODS

EVIDENCE FROM ALBANIA

Alba Kruja

Statistical Specialist at Shkodra Regional Office of Statistics (INSTAT) Part-Time Professor at “Luigj Gurakuqi” University , Shkoder, Albania alba_kruja@hotmail.com

Abstract

“Poverty has many faces, changing from place to place and across time, and has been

described in many ways. Most often, poverty is a situation people want to escape. So poverty

is a call to action -- for the poor and the wealthy alike -- a call to change the world so that

many more may have enough to eat, adequate shelter, access to education and health,

protection from violence, and a voice in what happens in their communities.”

World Bank Group, Poverty Net, Understanding Poverty

This paper survey the monetary approach to poverty measurement – a set of techniques and methodologies, adopted mostly by economist, based on the identification of poverty with a shortfall in a monetary indicator and the “objective” derivation of a poverty line. Significant progress has been made in the last decades with conceptualization of poverty and measuring it.We firstly need an explanation of what we mean by “monetary approach” to poverty measurement. All poverty indicators, wether based on monetary poverty or capabilities, wether uni-dimensional or multidimensional, aim to measure the individual’s welfare. Monetary poverty measuring command over market goods and services is by far the most widely used poverty measure. Easy to understand indicators allowing for comparisons over time and across regions and linked to household’s current economic conditions. Exist three main categories poverty measurements: 1.Technical objectives, 2.Aiming at changing the dominant discourse, 3.Advocacy. In empirical applications, non-monetary dimensions that have not been measured before are rarely considered. The analysis for Albania case is based on data from Institute of Statistics, INSTAT, by their surveys like:

1. Statistics on Income and Living Conditions (EU-SILC). SILC Instrument provides two types of data: a. Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions. b. Longitudinal data pertaining to individual-level changes over time, observed periodically over a four-year period.

2. Household budget survey (HBS)

Keywords: poverty line, monetary approach, non monetary poverty, welfare.

Objective

The objective of this document is to give an overview of the most well known methods

for measuring poverty, focussing in greater depth on those that are normally used within the

context of official statistics in the European Union.

1. What is “Poverty”?

Poverty is not a self-defining concept. Poverty is a complicated and multi-dimensional

phenomenon that goes beyond the monetary aspects. It is associated with poor economies,

poor human resources, poor social services provision, and socio-economic development.

A person (or household) is considered poor if the person’s (or household’s) income cannot

acquire the basket of goods and services used to define a threshold for poverty. The monetary

value of the basket is the poverty line and the population of people and households whose

incomes are below this line, is then derived through a head count.

2. Why do we need poverty measurements

Following Birdsall (2011), the purpose of welfare indicators can be classified :

Poverty indicators should help define more effective policies.

These indicators should have technical specifications that allow to:

1. compare the poverty levels of different households/individuals, and regions

within a country;

2. compare the evolution of poverty over time;

3. compare poverty levels between countries;

4. assess the impact of public policies.

3. Key Questions to ask when measuring poverty

Income or consumption aggregate:

Which module of the household survey is better developed, income or consumption?

The majority of authors suggested the use of both monetary measures or their combination in

assessing the poverty, and many more. In the last few years in Europe, income has been used

as the official variable for the compilation of statistics on poverty and social exclusion.

(i) Annual income, reflects a household's economic capacity, but it only provides a

partial view. As well as income, households have goods, assets, etc, which also form

part of their total wealth and influence the standard of living that households can

support. Income is considered a good proxy variable for a household's resources and

its possible access to certain living conditions.

(ii) The expenditure variable is more stable, expenditure depends more on the concept of

permanent income (expected future income or income that will allow families to live

in the same conditions without modifying their wealth) than on actual income.

Poverty line

Does a poverty line already exist in the country? Which poverty line is used:

absolute or relative?

(i) The absolute poverty refers to a minimum income threshold below which

individuals cannot meet their basic needs that are vital for survival.

Orshansky (1965) was the first to bring the concept of the line of absolute

poverty. Populations or households that live below the food poverty line are

considered to be in absolute and extreme poverty (also severe poverty and

sometimes chronic poverty.

(ii) Relative poverty compares the person or household’s income (expenditure) to

the income distribution of the country of residence. For instance, the Eurostat

uses a relative poverty measure based on “economic distance” wich

corresponds to a level of income set at 60% of the median household income.

Townsend (1979) created the relatively approach for poverty

measurements.

“Each country defines its own poverty line, based on the estimated cost of a defined minimum

of food and non-food consumption. Poverty data is not comparable between two groups,

because they are based on different surveys for data collection and because the poverty

analysis uses different methodology.”

In Albania it is calculated the absolute poverty line based on the consumption as a better

measure till now. The percentage of the poor people based on the absolute poverty line is

14.3 %. This percentage measured by relative poverty as people that live under 60% of

median per capita consumption is 12.2 %.

4. Traditional Measures of Poverty

Some measures of poverty are more frequently used in the literature compared to others.

a) Poverty Gap Index- measures the depth of poverty that is how far, on average,

households/individuals fall below the poverty line. This indicator presents the

minimum cost for eliminating poverty with monetary transfers.

b) Squared Poverty Gap Index- is used to measure the severity of poverty that is the

degree of inequality amongst the poor themselves.

c) Gini Coefficient- is based on the Lorenz curve, which is a cumulative frequency

curve comparing the distribution of a specific variable ( income for example) against

the population with the aim of showing inequality.

d) Growth Inciedence Curve- illustrates the decomposition of growth across different

income groups by presenting the impact of growth on poverty. The GIC plots the

growth rate at each quintile of per capita income.

e) The Watss Index- was proposed by Watts( 1968) and it is the average difference

between the logarithm of the poverty line and the logarithm of incomes.

4.1 Alternative Tools for Poverty Evaluation

a) Human Poverty Index- was introduced in the 1997 by Human Development

Report, consists of three dimensions: 1) a long and healthy life , 2) knowledge, 3)

a decent standart of living. But in 2010 HPI was replaced with the

Multidimensional Poverty Index.

b) Multidimensional Poverty Index- used for the first time in the 2010 UNDP

Human Development Report complements monetary measures of poverty by

taking into account multiple deprivations and their overlap. The global

Multidimensional Poverty Index (MPI) was created using the multidimensional

measurement method of Alkire and Foster (AF). The index examines deprivations

across the same three indicators –education, health and standard of living. The

global MPI covers 105 countries in total, which are home to 77 per cent of the

world’s population, or 5.7 billion people. Of this proportion, 23 per cent of people

(1.3 billion) are identified as multidimensionally poor.The MPI can also be

constructed by region, ethnicity as well as other groupings.

Dimension Indicator A person in a household is

deprived if…. Nutrition Any woman or child in the

Health

household with nutritional information is undernourished

Mortality Any child has died in the household

Education Schooling No household member has completed five years of schooling

attendance Any school-aged child in the household is not attending school up to class 8

Standart of Living

Electricity The household has no electricity

Sanitation The household’s sanitation facility is not improved or it is shared with other households

Water The household does not have access to safe drinking water or safe water is more than 30 minutes walk round up

Flooring Material The household has a dirt, sand or dung floor

Cooking fuel The household cooks with dung, wood or charcoal

Assets The household does not own more than one of: radio, telephone,tv,bike,motorbike,or refrigerator, and does not own a car or truck.

Source: Alkire, Roche, and Seth (2011)

A household is identified as multidimensional poor only if the person’s weighted

deprivation score is equal to or higher than the poverty cutoff of 33.33%. MDP

combines two aspects of poverty:

a) The expansion of poverty, shown as a percentage of poor people (H) and

b) The intensity of poor people, the average percentage of dimensions poor people are

deprived of (A).

Following the AF methodology, the MPI is calculated by multiplying the incidence of

poverty (H) and the average intensity of poverty (A),

M P I = H × A,

reflecting both the share of people in poverty and the degree to which they are deprived.

Table 1. Global MPI in Albania

Source: DHS, years 2008-2009, Global MPI Country Briefing,Albania

Figure1 : Headcount Ratios by poverty Measures

Source: DHS, 2008-2009.

Monetary poverty measures are the most recent estimates from the World Bank(2018),

Monetary poverty measure refer to 2012 (1.9 $ a day), 2012 (3.10 $ a day) and 2012 (national

measures)

Figure 2: Poverty Headcount Ratios

Source: Global MPI Country Briefing 2018, www.opgi.org.uk

Figure 2 compares the headcount ratios of the global MPI and monetary poverty measures.

The height of the first bar of figure 2 shows the percentage of people who are MPI poor. The

second and third bars represent the percentage of people who are poor according to the World

Bank’s $1.90 a day and $3.10 a day poverty line. The final bar denotes the percentage of

people who are poor according to the national income or consumption and expenditure

poverty measures.

Figure 3: Share of People by minimum Deprivation Score

Source: DHS year 2008-2009, own calculations.

Category 33.3+% is equivalent to headcount ratio of global MPI, category 50+% corresponds

to Severe Poverty of global MPI.

Figure 4 : Indicator Contribution to Overall Poverty By Area, Albania

Source: DHS, years 2008-2009, Global MPI Country Briefing,Albania

Figure 4 contains two bar graphs that compare the percentage contribution of each indicator

to national, rural and urban poverty. In the bar graph on the left-hand side, colors inside each

bar denote the percentage contribution of each indicator to the overall MPI, and all bars add

up to 100%. In the bar graph on the right, the height of each bar shows the contribution of

each indicator to MPI. This enables an immediate visual comparison of the composition of

poverty across areas.

Figure 5: National MPI, Albania

Source: Global MPI Country Briefing 2018, www.opgi.org.uk

Dark red indicates a higher MPI and therefore greater poverty, while dark green indicates a

lower MPI and therefore lower poverty in Albania.

5. Types of Data

1. National level-data- including national accounts: GDP, consumption, investment,

exports, imports, public finance data, consumer and producer prices.

2. Local-level data- including consumer and producer prices, national accounts at

regional level.

3. Individual and household-level data-household consumption and income;living

conditions;social indicators. Population Statistics (census), household living standards

(helath survey), household priorities, perceptions of well-being ( qualitative studies).

4. Administrative data- can often provide an important entry into poverty analysis,

especially if such data are used to compare need and demand for services. However

do not allow for cross-tabulating or analyzing poverty across different dimensions.

5. Population census- use the information on all citizens of a country. The census is

carried out for all household to obtain basic information on the population, its

demographic structure, and its location. Since the census covers the wole population it

is costly, and most countries conduct a census only once a decade. Information on

household income, consumption, disease patterns, and poverty perceptions are

generally not included. The usefulness of sample surveys can be increased

substantially if they are combined with census information , such as for providing

poverty maps.

Countries of EU member and aspiring to EU membership collect data through EU Surveys

on Income and Living Conditions (SILC), and use relative poverty measurement , where

the “ at risk of poverty” threshold is determined as 60 % of median disposable household

income. Meanwhile other countries of this group use Household Budget Surveys (HBS).

6. Household survey

Household surveys are essential for the analysis of welfare distribution and poverty

characteristics. Household survey covers a small fraction of all households. This sample must

be carefully chosen so that the results of the survey nevertheless accurately describe living

conditions in the country and in different parts of the country. The sample size- the number of

households interviewed-will vary with several factors, including the indicator to be measured.

Although many different surveys can be used for poverty and welfare analysis, a multitopic

survey is a key tool for measuring and understanding a wide range of issues related to

poverty.

Different types of household survey exist:

1- Living Standart Measurement Study (LSMS) surveys, collect information on

household expenditures and income, health, education, employment, the ownership of

assets such as housing or land.

2- Expenditure and income surveys- they are useful to measure different dimensions

of poverty, such as income or education poverty.

3- Employment surveys- questions about household income, demographics and housing

features.

4- Demographic and Health Surveys-also contain basic data about housing conditions,

educational attainments,and employment patterns, they don’t include income or

expenditure data.

7. What’s your share of the pie?

Data from the OECD Income Distribution Database (oe.cd/idd). More than 2M users :

http://www.compareyourincome.org/

Interactive web-tool launched in 2015 to:

a. Inform and engage citizens

b. Collect information on people’s perceptions of income inequality in their country 36

OECD countries + 4 emerging economies

c. Information on country of residence, household income, age, gender and household

size also provided

8. Poverty Data collecting in Albania

In the last two decades poverty indicators in Albania were calculated on the basis of data collected within Living Standards Measurement Survey (LSMS), today EU-SILC and

Household Budget Survey (HBS), which has been conducted continuously from 2014 . Since 2003, European Union member states use Statistics on Income and Living Conditions (EU-SILC) for data collection related to living standards and poverty measurement. This survey (LSMS) has had its concept of poverty measurement based on the cost method, while the EU-SILC survey aims to measure poverty based on the income method and ensure comparability of indicators with the countries of Europe. The Living Standard Measurement Survey (LSMS) is the only source of information to measure the

living standard, poverty, and wellbeing of Albanian household until 2012. This survey collects a

series of monetary and non-monetary indicators, bringing a variety of information to different users,

and provides a necessary tool for policy maker and strategies. LSMS was conducted for the first time

in 2002, followed by two other surveys every three years, respectively in 2005, 2008 and 2012

(INSTAT, 2013).

Given the growing need to obtain highly comparable data in the European Union and the

desire to improve the EUHP, a new statistical source "Statistics on Income and Living

Conditions (EU-SILC)" was created, which ensured a higher level of data harmonisation in

the survey and allowed for greater measurement of poverty and living conditions. With this

aim in mind, a regulation framework from the European Parliament and Council was

developed, as well as various Commission regulations that regulate all aspects of the process

up until the final collection of data (regulations on the sample and field work, definitions,

variables and quality reports). Via these regulations, good quality and a high level of

comparability between countries is ensured. In Albania , the EU-SILC began to be carried out

annually in 2016.

8.1 EU-SILC in Albania

INSTAT in December 2014, a pilot survey conducted where a sample of 600 families was selected. INSTAT conducted the first full SILC in 2016 using paper questionnaires. The champion is selected by lot using the two-stage selection. As a base of elections served the Census of Population and Housing October 2011. In the first step, 768 census areas were randomly allocated to urban and rural areas. In the second step with systemic choices, 12 families were selected in each census area selected in the first step.

After piloting the CAPI method in 2017, INSTAT concluded that for a panel survey it is

more efficient to use this method. In the end of 2017, INSTAT conducted a second wave of

SILC using CAPI method. In April 2018, INSTAT conduct the third wave of SILC, and in

Aprial 2019 we are waiting to get started the fourth wave of SILC, periods 1 April-31 July.

The reference population of EU-SILC is all private households and their members residing in

the territory of the country at the time of data collection. The size of sampling for Albania:

2016 9216 families

2017 7539 families 2018 7791 families

SILC provides two types of annual data:

Cross-sectional data pertaining to a given time or a certain time period with variables on income, poverty, social exclusion and other living conditions, and

Longitudinal data pertaining to individual-level changes over time, observed periodically over a four year period.

MODES OF DATA COLLECTION

As for the interviews, there are four different ways to collect the data:

1) Paper-Assisted Personal Interview (PAPI),

2) Computer-Assisted Personal Interview (CAPI),

3) Computer-Assisted Telephone Interview (CATI)

4) and Self-administrated questionnaire.

Figure 6 shows the different modes of data collection used by the countries for the 2013 EU-SILC cross-sectional operation. Figures are obtained adding up the number of interviews carried out by each mode of data collection by each country and dividing it by the total of the interviews carried out in each country. Only face-to-face interviews are taken into account.

Figure 6: Different Modes of data,EU-SILC

Source: Eurostat

In Albania the survey is conducted using two types of questionnaire, using CAPI method

since 2017:

i. Household questionnaire;

a) Dwelling and housing conditions;

b) Expenditures on the dwelling in which the household lives (repayments of loans

and credits for purchasing the dwelling, costs for electricity, heating, repairs and

others);

c) Arrears of the households (possession of durable goods, capacity to face

unexpected financial expenses and others);

d) Income at household level: – Income of persons up to 16 years old; – Social

transfers received (social benefits and allowances); – Given and received

resources in cash or in kind; – Income from agricultural activity.

ii. Individual questionnaire for each member of the household aged 16 and more

a) Working life;

b) Economic activity, employment and unemployment at the time of the

interview;

c) Information on the main and additional employment (second, third job) of

those who work;

d) Current monthly income from employment;

e) Information on the last job of unemployed and inactive persons;

f) Gross and net income for the previous year, received from different sources

(employment, pension, benefits, sale or rental of movables or real estate and

others);

g) Self-perceived health and access to healthcare.

8.2 HBS-House Budget Survey in Albania

Household Budget Survey is a statistical survey carried out at the Albanian usual resident

households and gives a clear overview of the socio-economic situation of the Albanian

households. The main purpose of the data collection is to estimate the level and structure of

income, consumption expenditure in the country as a whole as well aggregated by prefecture

level. The HBS data are used also for the calculation of the consumer price index and to

estimate the private final consumption expenditure of the household sector in the National

Accounts. The maintenance of a detailed diary of the household expenditures over a two-

week period (until 2019 year), meanwhile in 2019 over one-week period, by the surveyed

households .

(i) Sector Coverage

The main groups of consumption:

1.Food and Non-Alcoholic beverages

2.Alcoholic beverages and Tobacco

3.Clothing and footwear

4.Housing,water,electricity and other fuels

5.Furnishing, household equipment

6.Health

7.Transport

8.Communication

9.Recreation and Culture

10.Education

11.Restaurants and hotels

12.Miscellaneous goods and services

(ii) Comparability over time

The household Budget Survey was conducted by INSTAT :

2006-2007

2008-2009

2014- till now , every year.

(iii) Data collection

Data collection is based on two different ways of collecting the information:

Completing a diary of purchases

Conduct a direct interview through the interviewers in the first week of the following

month reference period.

(iv) The sample selection

The sample selection is done in a two-step procedure. The Units of the First Step are Homogenized Census Areas [1], with a probability proportional to the size of the Census Area. In the second step, within each of the selected areas in the first step, a fixed number of 12 census area is selected according to the systematic random selection method. The choice in both steps is done at random by providing a representation at the regional level. The total number of sampled areas is divided into 4 sub-three-month samples that are geographically distributed homogeneously throughout the year to include seasonal changes.

Table 2: The structure of consumer spending in families (In ALL)

Source: INSTAT, 2019

Conclusion

One of the five headline targets of the Europe 2020 strategy is to reduce poverty by lifting at

least 20 million people out of the risk of poverty or social exclusion by 2020.

The headline Targets of the Europe to monitor this poverty target is the AROPE indicator “at

risk of poverty or social exclusion”, showing people who face at least one of the following

conditions:

They are at risk of living in income poverty after social transfers (their equivalised

disposable income is below their national at‐risk‐of‐poverty threshold, which is set at 60% of

the national median equivalised disposable income);

They are severely materially deprived—they cannot afford at least four of nine items

deemed to be essentials

They live in households with very low work intensity (defined as people from 0–59 years

of age living in households where adults [those aged 18–59, but excluding students aged 18–24] worked less than 20% of their total potential during the previous 12 months).

Albania transitioning from its LSMS to SILC-based reporting. Also Albania is working to

mitigate the differences between the two surveys in thematic and geographic coverage, level

of representation, non-response rate and periodicity, and INSTAT and World Bank are

exploring the possibility of estimating absolute poverty rates using the annual HBS,. This

would facilitate consistency in producing consumption-based poverty data, and fulfil the need

for longer data series, potentially helping with continuity of monitoring and evaluating

national policies that were planned and implemented based on the absolute poverty line

measured through the LSMS.

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