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1 DEPARTMENT OF ECONOMICS Uppsala University C-Thesis Spring 2010 Economic development in ex-Yugoslavia -Some good advices on the way Author: Linda Wiese Supervisor: Niklas Bengtsson

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DEPARTMENT OF ECONOMICS

Uppsala University

C-Thesis

Spring 2010

Economic development in ex-Yugoslavia

-Some good advices on the way

Author: Linda Wiese

Supervisor: Niklas Bengtsson

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ABSTRACT

This thesis will determine the factors that have affected the economy in the countries from ex-

Yugoslavia. A couple of regression analyses will test the correlation between GDP Growth or

GDP per Capita and twelve independent variables. The analyses tell us that high import ratio,

low inflation and not being in an intrastate war are associated with high GDP Growth, where

high political rights, being a member of the European Union or having a status as a Candidate

Country are associated with high GDP per Capita. The explanation for the different result

might be the catch up effect.

Key Words: GDP Growth, GDP per Capita, Regression Analysis, Yugoslavia

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Table of contents:

1.1 Introduction 4

1.2 Purpose and framing of the question 4

1.3 Disposition 5

2.1 Method 6

2.2 Why the states from the Socialist Federal Republic of Yugoslavia? 7

3.1 Socialist Federal Republic of Yugoslavia: Modern History 8

3.2 Economy in Socialist Federal Republic of Yugoslavia 10

3.3 Country Profiles 11

3.4 GDP Growth in the countries from the SFRY 13

3.5 GDP per Capita in the Countries from the SFRY 15

4 Discourse Relating, Material, Variables and Operationalization 16

4.1 Political rights 16

4.2 Civil Liberty 16

4.3 European Union 17

4.4 Candidate Country 17

4.5 Export ratio of GDP 18

4.6 Import ratio of GDP 18

4.7 Military Expenditure 18

4.8 Internet access 19

4.9 Conflicts or Intrastate Wars 19

4.10 Inflation 20

4.11 Year 20

4.12 Population 21

5 The GDP growth and per Capita 22

6 Limitations 23

7 Result 24

7.1 Correlation Matrix: Independent Variables 24

7.2 GDP Growth 25

7.2.1 GDP Growth: Multiple Regression Analysis 25

7.2.2 GDP Growth: Simple Regression 26

7.2.3 GDP Growth: Controlling for Variables 27

7.3 GDP per Capita__ 29

7.3.1 GDP per Capita: Simple Regression Analysis 30

7.3.2 GDP per Capita: Multiple Regression Analysis 30

7.3.3 GDP per Capita: Controlling for Variables 31

8 Summarize and Conclusion 33

9 List of source 35

Appendix 1: Multiple Regression Analyses 38

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1.1 Introduction

During the last two decades, the map of Europe has been updated many times. Big states have

been split into smaller states, federations have been constituted and dissolved and pacts and

unions have been created. At the same time, the world has shrunk and the distance between east

and west has declined. The states which previously belonged to the “poor east” are all of the

sudden prepared to start the association process for the European Union.

In this essay, I will focus on the countries from the Socialist Federal Republic of

Yugoslavia (SFRY) and their economic growth. Yugoslavia broke up in the early nineties and

gradually, six countries were constituted (seven, if one includes Kosovo). When comparing the

GDP growth in each country, one can conclude that the economic development has differed in

the different countries. Therefore, my assignment will be to investigate the different factors that

have affected the economy in these countries.

1.2 Purpose and framing of the question

The purpose of this essay is to determine the main factors for the economic growth in Ex-

Yugoslavia. From seven theories I will develop ten statements, which will help me to determine

the difference in economic growth. I will transform these statements into variables and test

these on my selected counties through a couple of regression analyses. Hopefully, the result

will tell my something about the explanation power in these variables. My main question will

be as following:

Which factors can best explain the differences in economic growth in the states from the

Socialist Federal Republic of Yugoslavia

The countries I will study are Slovenia, Croatia, Serbia, Montenegro, Macedonia and Bosnia-

Herzegovina. Since I do not have any information about the GDP growth in Kosovo, I have not

been able to include Kosovo in my study. However, since Kosovo only has existed since 2008

and I will analyze the time between 1991 and 2008, it would be difficult to measure the

economic growth anyway.

My ambitions are not primary generalization. Since I test already existing theories, the

ambitions are rather to determine if the existing theories are applicable on the countries in ex-

Yugoslavia. Perhaps my result can tell something about new created countries in general or

countries in Eastern Europe in particular?

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1.3 Disposition

I will start my study with the introduction, the Purpose and framing of the question and the

disposition. In the second section, I will discuss the method I will use and why I chose Ex-

Yugoslavia. In the third section, I will give a short breath about the history of the ex-

Yugoslavia, their economic history and the economy today in the different countries. I will also

discuss their GDP Growth and their GDP per Capita for the last twenty years.

In the fourth part, I will discuss seven earlier studies that other economist and political

scientists have developed. Further, from their studies, I will develop ten variables which I will

operationalize. I will also discuss how to measure them and the material I will use. I will add

two “control variables”; year and population.

In the fifth section, I will discuss the dependent variables: GDP growth and GDP per

Capita, how I will operationalize them and the material I will use when measuring them. In the

sixth part, I will discuss some variables I have chosen to exclude and some other limitations in

the study.

In the seventh part, I will discuss the regression analyzes and the result I have get. I will

analyze both the GDP Growth and the GDP per Capita. And in the eighth part, I will

summarize my result, compare the GDP Growth and the GDP per Capita and try to draw some

conclusions from the study.

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2.1 Method

I core method will be regression analyses. Through the regression analyses, I will test my

independent variables to determine which ones that best can explain the GDP growth in Ex-

Yugoslavia. The independent variables will originate from earlier studies about GDP growth. I

will discuss the earlier studies more in detail in the fourth section.

From the earlier studies, I will develop ten statements, which I will analyze. I will start the

analysis by a correlation matrix, to determine if there exists any correlation between the

variables. Then, I will do a multiple regression analysis and a couple of simple regression

analyses and finally some more analyses where I will control for anticipatory variables.

After these analyses, I will do a comparing analysis where I change the variable “GDP

growth” to “GDP per Capita”: GDP per Capita is another measure to rate how “rich” the

countries are. Also here, I will do a multiple regression analysis, some simple regression

analyses and some analyses where I control for anticipatory variables.

The independent variables will be coded as either a dummy variable or through an index (see

the fourths section for more details). The dependent variable is either the GDP growth or the

GDP per Capita for the countries. Since the number of countries is limited, I will analyze every

year between 1991 and 2008. For some countries, I do not have data for all years. In these

cases, I will analyze the year I have data for.

The statistic program I will use is STATA. Mainly, I will analyze the coefficients, the standard

error, the R2 and the p-value for the variables.

The Coefficient explains how many percentage point the dependent variable will increase

(or decrease) when the independent variable increases one percentage point.

The Regression Standard Error measures the precision of the coefficient. If the

Regression Standard Error is low, the precision of the coefficient is high.

The R2 explains the proportion of explained variance. In other words, it explains the

proportion of the variance in the dependent variable which could be explained by the

independent variables.

The P-value explains the probability to observe a more extreme value than the one we

observed if the correlation we tested for is equal to zero. In other words, a high p-value

indicates that the result only is significant on a high significant level.

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2.2 Why I chose the states from the Socialist Federal Republic of Yugoslavia?

Why did chose to investigate the countries from Ex-Yugoslavia? There are many reasons for

that. First, since all states originate from one federation, one can assume that the states have a

similar background. Further, the countries represent the acculturation of Eastern and Western

Europe and the integration process when the European Union is enlarging, which make it up to

the minute to study. The countries has reach different step in the association process; Slovenia

is a full member, Croatia and Macedonia have the status as candidate countries, where other

states have showed more or less interest to join the union. Since good economy is a

requirement for joining the EU, investigating why the states has so different economic growth

could help them to increase the economic development and step closer to EU (if they want). I

would not say that the countries from ex-Yugoslavia would represent all new established

countries in the world, but this study can tell us something about the reasons for why new

establisched countries have different economic growth.

When writing about new-constituted states, the question “when is a state a state?” will always

arise. For instance, Sweden recognized Kosovo as a state quite early, where other states have

not recognized Kosovo yet. The problem in my research arose when one source counts a state

for one state when another source counts it as two separate states. For instance, according to

Freedom House, after the first split of Yugoslavia (1991), the Federal Republic of Yugoslavia

was created. In 2003, the republic changed name to Serbia-Montenegro and in 2007, the

republic was split into Serbia and Montenegro. On the other hand, the World Bank has counted

it as two states already in 1997, and has declared the GDP for two states from 1997. I have

resolved the problem by applying the freedom House Index from the Federal Republic of

Yugoslavia and Serbia-Montenegro to Serbia and Montenegro. As I conclusion, I will count it

as two separate states from 1997.

When I discuss about the states from the Socialist Federal Republic of Yugoslavia (SFRY), the

Balkan Peninsula or the ex-Yugoslavia, I am referring to the same thing.

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3.1 Socialist Federal Republic of Yugoslavia: Modern History

After the Second World War, the Socialist Federal Republic of Yugoslavia (SFRY) was

created, consisting of sex republics: Bosnia-Herzegovina, Croatia, Macedonia, Montenegro,

Serbia and Slovenia. In 1974, two new provinces resided in Serbia: Kosovo and Vojvodina.

The communist Parties in the republics were independent in relation to the federal party: The

Yugoslav League of Communists (YLC). The decision-making system was decentralized and

the republic parties had veto power in some of the federal decisions: important economic

questions, ratifications of agreement with other states, modifications in the constitution or

borderlines between the republics. In 1988, Kosovo and Vojvodina lost their autonomous status

and amounted politically and administratively to Serbia.1

In 25 June 1991, due to the growing nationalism and democratization process which

swept through Eastern Europe, both Croatia and Slovenia declared their independence. These

declarations were not appreciated by SFRY and the Yugoslav National Army resisted the

independence of the two new states and violence occurred. The European Community2 had to

assume the principal mediation role to solve the conflict.3

The European Community (EC) set a new regime for recognition of states in the “Eastern

Europe and the Soviet Union”. For Yugoslavia, any of the republics which wished to be

recognized as an independent state had to apply for recognition in 23 December 1991. Of all

six Yugoslav republics, only four sought recognition. In January 1992, the European

Commission decided to recognize Croatia and Slovenia as independent states. In the next few

days, other states followed the extend recognition.4

In April 1992, a referendum about the state’s independence was held in Bosnia-

Herzegovina. In 7 April 1992, the EC and the US moved to recognize Bosnia-Herzegovina.

After that, many other countries were following the recognition.5 Also here, the Federal

government opposed the secession and violence erupted until April 1994. The tensions in

Bosnia led to the massacre in Srebrenica in July 1995, when Bosnian-Serb forces massacred

and killed over 5000 Bosnian-Muslim men. The conflict ended when NATO decided to bomb

the Bosnian-Serb territories and in October, the peace was declared.6

1 Karlsson: 93:35

2 The first of the three pillars in the European Union, existed independent 1957-1993 (Britannica Online

Encyclopedia: European Community). 3 Rich 1993:38-40

4 Rich 1993:43-49

5 Rich 1993:50-51

6 Nationalencyklopedin online: Jugoslaviska Krigen

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The question about the recognition of Macedonia was slightly more complicated for the

EC. In January 1992, the UC decided not to recognize the state.7 One problem was the name

issue: Greece could not accept the name Macedonia because it indicated a revival of claims on

Greek Macedonia. As a compromise, in 1993, the state joined the United Nation under the

name the Former Yugoslav Republic of Macedonia.8

Serbia and Montenegro did not seek recognition from the international community.

Instead, on April 1992, the Assembly promulgated that SFRY had transformed into FRY,

Federal Republic of Yugoslavia¸ consisting of two states.9 In February 2003, the federation

changed its name to the Federation of Serbia and Montenegro. In 2006, a referendum was held

in Montenegro and on 3 June, the independence and the separation from Serbia were

declared.10

Less than two years after the disunion of the federation, Kosovo declared its

independence in 17 February 2008. The state had fought for its independence since 1996.11

It is

too early to call the territory a sovereign state and the European Union is divided about the

status for Kosovo. Serbia does not recognize Kosovo as a sovereign state.12

Slovenia is the only country from the ex-Yugoslavia which has joined the European Union. The

country got the status as a candidate country in 1998 and the first may 2004, Slovenia joined

the EU. In February 2002, Croatia applied for a membership. One and a half year later, the

country got the status as a candidate country.13

The negotiation with Croatia is now on its final

states and the country has good chances to join the Union in 2011.14

In Mars 2004, Macedonia (FYROM) applied for a membership in the European Union. In

December the next year, the country got the status as a Candidate Country, but no date is set for

the start of the negotiation. During 2009, Serbia applied for a membership of the European

Union. Montenegro is also on its way to start the negotiations.15

Even Bosnia-Herzegovina is a

potential Candidate Country, but the state has a long way to go. If Kosovo wants to join the

Union, a lot of reforms have to be done.16

7 Rich 1993:52

8 Britannica Online Encyclopedia: Macedonia

9 Rich 53

10 Britannica Online Encyclopedia: Serbia The federation of Serbia and Montenegro

11 Nationalencyklopedin online: Jugoslaviska Krigen

12 Tansey 2009:153-154

13 Regeringen: EU:s utvidgning

14 EU:s Förbindelse med Omvärlden - 14/10/2009

15 Regeringen: EU:s utvidgning

16 EU:s Förbindelse med Omvärlden - 14/10/2009

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3.2 The Economy in Socialist Federal Republic of Yugoslavia

According to Horvat, the economic history in Yugoslavia could be divided into three periods:

1911-40: Capitalism, 1940-54: Central Planning and 1954-today: Self-government Socialism.

The Centrally Planned Economy involved nationalization of private capital in industry, mining

and transport. Later it also included retail trade and houses with more than three apartments,

but the economic growth was on average negative.17

In June 1946, plan economy was introduced by law. The federal Planning Commission

had prepared the plans and was responsible directly to the Federal Government. The plans for

Yugoslavia were extremely ambitious; the national income should be doubled compared to the

pre-war level. The idea of the planning was copied from the Soviet, but the blueprint did not

produce the expected result and the expected economic growth default.18

In the early fiftieth the state prepared for the New Economic System (NES). NES was

implemented in 1952 and was transitional in character and lasted until 1960. During this period,

the GDP Growth was 8,5 percent per annum and the federation had the highest economic

growth in the world. The economy of the federation was still regimented by plans, but the plans

were more decentralized.19

According to Sapir, during the period 1953-65, Yugoslavia had a

better economic growth on average than other economies at similar levels of development, both

in terms of output and of total factor productivity growth rates.20

In the early sixtieth, the economy was booming: self-management in enterprises was

established and three radical reforms were implemented to increase the economy even more.

The system of multiple exchanges rates was replaces by a customs tariff, the Dinar was

devaluated and the foreign trade was liberalized. Further, the federation became an associated

member of General Agreement on Tariffs and Trade (GATT). These three reforms in 1961

were the beginning of the third phase of the economic development.21

The three reforms from 1961 were poorly prepared and badly implemented and the

economy started to decline. The federation had to pump money into the economy and in 1963;

the economy was back to normal. At the same time, the new constitution was implemented,

which was decentralization-oriented and guaranteed more self-government for the states. These

led to a new economic boom in 1964, which ended with a heavy inflation and great balance of

payments deficit. In the early 1965, the solution of the economic problems was further self-

17

Horvat:1971:73, 92 18

Horvat 1971:74-76 19

Horvat 1971:77 20

Sapir 1980:294 21

Horvat 1971:82

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government autonomy, a more competitive market and further integration in the world

economy. These reforms were aimed to be economic but the result was both social and

political.22

The transition to market economy involved a lot of problems for the Eastern European

countries. The countries were not enough prepared for the private section growth and new

structures takes time to develop. In the late eighties, the economy in Yugoslavia grew less

compared to other EEC countries, with the exception of Slovenia and Croatia, where the

economic restructuring had gone more rapidly. In 1991, federal government collapsed and the

economy became decentralized.23

All countries from SFRY is taking part in the socialist self-management system, which

amounts that business enterprises, banks, administration, social services, hospitals, and other

working bodies are intended to be run by elected workers-councils, which in turn elected the

management boards of the bodies. The level of the workers’ control varies between different

enterprises, since a lot of workers are more interesting in hiring, firing and benefits, rather than

business decisions.24

3.3 Country Profiles

Bosnia-Herzegovina: Due to the civil war which ended in 1995, the economy has been

declining and was described as “dire”. The economy has slowly started to grow and had in

2001 grown to 50 percent of the prewar level. Foreign trade deficit remained at over 60 percent

of GDP, but the foreign investment had hardly grown.25

In 1996, the GDP growth was

extremely high, almost 90 percent, due to the end of the war. After that, the GDP growth has

declined and has during the last ten year been stable around five percent. In 2008, The GNP per

capita was 4 900 US-dollar and in 2009, the GDP growth was 3.5 percent.26

Croatia: In 1993, the state implemented a successful stabilization policy to help the

industrialists in the country. Due to the companies “wait and see” attitude, the unemployment

was high and reached a level of 16,4 percent, as the same time as the foreign investment was

low (1994).27

During the last fifteen years, Croatia has achieved impressive economic and

social progress. The economy grew around 4-5 percent annually, even if the GDP only grew

22

Horvat 1971:82-83 23

Turnock 1997:167-169, 240-241 24

Britannica Encyclopedia online: Socialist Self-Management 25

Pugh 2002:468-469 26

World Bank: Bosnia and Herzegovina Country Brief 2010 27

Turnock 1997:244-245

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2,36 percent in 2008. At the same year, the GDP per capita was 15 600 US-dollar, which is 63

percent of the European Union average income level.28

Kosovo: Since June 29, 2009, Kosovo became the newest member of the World Bank Group

Institution. During the last ten years, the economic recovery has been significant. Kosovo went

through the global finance crises with a high economic growth and in 2008, the GDP growth

was 5,4 percent. The GDP per capita was only 3000 US-dollar, which make Kosovo to one of

the poorest country in Europe. Today, 45 percent of the population is counted as poor and 17

percent is counted as extremely poor.29

Macedonia: During the nineties, the government aimed to strengthen the banking by

privatization of the national bank and expanding the commercial banking. In 1995, the

privatization of companies increased and one year after, two third of the companies was private

owned. Since the end of the Greek blockade (due to the name-dispute) the foreign trade and

investment have increased.30

The economic performance in Macedonia has improved

considerable prior to the recent global economic crisis. In 2008, the GDP growth was five

percent and the GDP per Capita was 4700 US-dollar.31

Montenegro: The country has suffered hard from the transformation of the big federation to the

small federation, consisting of only Montenegro and Serbia. The country has had some

problems with smuggling (in particular tobacco) and this led to Italian trade sanctions.32

Since

the completely separation from Serbia, the economy has been broadly stable. The fiscal and

current account deficits remain unsustainably high and the external indebtedness has been

growing. In 2008, the GDP growth was 8,10 percent and the GDP per capita was 7900 US-

dollar.

Serbia: Since the annulment of the big Yugoslavian federation, Serbia has had a lot of problems

with separatism and intrastate wars, which have suffered its economy. Sanctions from the

surrounding world have not improved the situation. The divided ethnic composition and the

many resettles had led to a growing nationalism that devastated the economy and divided the

28

World Bank: Croatia Country Brief 2010 29

World Bank: Kosovo Country Brief 2010 30

Turnock 1997:246-248 31

World Bank: Macedonia Country Brief 2010 32

Turnock 1997:254-255

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country.33

Serbia is counted as a middle-income country, which during the last ten years had

started its democratic and economic reforms. In 2008, the GDP growth was 1,24 percent and

the GDP per capita was 6800 US-dollar.34

Slovenia: Slovenia is the most developed of the countries from ex-Yugoslavia and has always

been trade-targeted. After the separation from the federation, Slovenia lost some of the trade

market, but found soon a new trading-partner in form of the European Union: In 1995, more

than two third of the international trade was with EU. 35

The last ten years, the GDP growth had

been around four percent. In 2008, the GDP growth was 3,54 percent and the GDP per capita

was 27 000, which is the highest GNI per capita for all countries from the federation.36

3.4 GDP Growth in the Countries from the SFRY

Table I: GDP growth by country on average (percent)

Country GDP growth:

Bosnia-Herzegovina 15,55

Croatia 1,30

Macedonia 0,78

Montenegro 3,65

Serbia 1,12

Slovenia 3,60

As we see in table I, when we compare the countries which each other, the GDP growth on

average has differed between the countries. For instance, Bosnia-Herzegovina has had a GDP

growth which on average was twenty times bigger than Macedonia.

When we look at the GDP growth in the countries year by year, we can see the differences even

more. According to diagram I, Macedonia and Croatia and Slovenia have had a development

approximately the same during these years. They started with a negative GDP growth, but all of

them have changed it to a positive growth. Croatia stared with the lowest GDP growth of the

three ones and had the lowest GDP growth in 2008, but the three countries have changed the

ranks during these years and have in 2008 approximately the same GDP growth.

33

Turnock 1997:253-254 34

World Bank: Serbia Country Brief 2010 35

Lewinsson, Lindström, Svanberg and Östberg 1998:229-230 36

World Bank: Slovenia Data and Statistics for Slovenia

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Diagram I: GDP Growth in Slovenia, Croatia and Macedonia

According to Diagram II, Serbia started with a very low GDP growth. At that time, Serbia and

Montenegro was a unit state. Therefore, one can assume that Serbia’s GDP growth also

includes Montenegro’s during the first years. After they had split up in the 1998, the GDP

growth fellow the same process, in exception for the 2001, where Serbia has an extreme GDP

growth. Bosnia-Herzegovina had an even more extreme GDP growth in 1996, but has during

the last year fellow the same process as the other states. In 2008, all six states had a GDP

growth between one and eight percent.

Diagram II: GDP Growth in Bosnia-Herzegovina, Serbia and Montenegro

-25

-20

-15

-10

-5

0

5

10

1990 1995 2000 2005 2010 Slovenia

Croatia

Macedonia

-40

-20

0

20

40

60

80

100

1990 1995 2000 2005 2010

Bosnia-Herzegovina

Serbia

Montenegro

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3.5 GDP per Capita in the Countries from the SFRY

Table II: GDP per Capita on Average for all Years (US-dollar)

Bosnia-Herzegovina 1995

Croatia 6678

Macedonia 2306

Montenegro 3685

Serbia 3077

Slovenia 12801

As one can see in Table II, the GDP per Capita has differed between the countries. The

wealthiest country on average has been Slovenia and the poorest country on average has been

Bosnia-Herzegovina. Table I showed the same numbers, but for the GDP growth. In that table,

Bosnia-Herzegovina had the highest GDP growth, Macedonia had the lowest and Slovenia was

in the middle. It seems that it is easier for a poor country to increase its GDP and catch up.

Diagram III: GDP per Capita for each Country for all Years (US-dollar)

In Diagram III, one can see the GDP growth for each country and for each year. Here, one can

see that Slovenia has been the country with the highest GDP per Capita for every year and that

Croatia is number two for every year. The other four countries are more homogeneous and have

a lover GDP per Capita for every year. When comparing it with Diagram I and II which

showed the GDP Growth for the countries, the differences is big, since the GDP Growth is less

homogenous than the GDP per Capita.

0

5000

10000

15000

20000

25000

30000

1990 1995 2000 2005 2010

Bosnia-Herzegovina

Croatia

Macedonia

Montenegro

Serbia

Slovenia

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4 Discourse Relating, Material, Variables and Operationalization

In this section, I will construct the statement from the theories. I will also discuss them briefly

and operationalize them. I will conclude the variables in table III.

4.1 Political rights

According to Prezeworski, Alvarez, Cheibub and Limongi, democracy and economic

development are walking hand-in-hand. In Democracy and Development, they have studied and

analyzed 127 countries between 1950 and 1940 and drew some conclusions about the

relationship between democracy and economic growth. According to this study, income per

capita grew faster in democracies compared to dictatorships, not because the total national

economic growth is affected, but because the population is growing faster than the economy in

the dictatorships compared to the democracies.37

From Prezeworski’s et al theory about the correlation between democracy and economic

development, I have constructed S1.

S1: A low score in the Political Right index is correlated with an increased GDP growth.

When I test this statement, I will measure the correlation between Political Rights and

economic growth. I will use the Political Rights index from Freedom House (FH). This index is

coded 1-7, where seven is full democracy and one is dictatorship. FH rates for the real-world

rights and freedoms enjoyed by individuals. Even if FH considers the presence of legal rights,

they place a greater emphasis on whether these rights are implemented in practice or not. The

political rights index is coded from ten questions, grouped into three subcategories: Electoral

Process (3 questions), Political Pluralism and Participation (4), and Functioning of Government

(3). From these questions, they have coded the states as 1-7.38

4.2 Civil Liberty

Since Civil Liberty is connected to democracy, I will investigate if the grade of Civil Rights has

any impact on the economic development. This variable is also developed from Prezeworski’s

et al and the statement will be:

S2: A low score in the Civil Liberty index is correlated with an increased GDP growth.

37

Prezeworski et al 2000:1-10, 136-137, 178-179 38

Freedom House Analysis Freedom in the World Methology

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I will use the FH:s index for Civil Liberty, coded 1-7. The civil liberties questions are coded

from fifteen questions and grouped into four subcategories: Freedom of Expression and Belief

(4 questions), Associational and Organizational Rights (3), Rule of Law (4), and Personal

Autonomy and Individual Rights (4).39

4.3 European Union

Neck, Haber; and Mckibbin, have analyzed the impact of the association process or a

membership in EU for the Eastern and Central European (EEC) countries and conclude that

both would have a positive effect of the economic development. Since the tariffs between EU

and the EEC countries use to be relatively low, the main macroeconomics effects would come

from the participation in the European Single Market. Through a Mckibbin-Sachs Global

Model (MSG2)40

, Neck et al have quantified the macroeconomic consequences of the EU

association process on the EEC countries. Their conclusion is that the European Union

association would, due to the spillover effect, lead to a higher GDP for the Eastern and Central

European countries.41

From this study, I will develop the third statement:

S3: Being a member of the European Union is correlated with an increased GDP growth.

When I analysis the relationship between the membership in the EU and the GDP growth, I will

use a dummy variable and code “one” for being a member in the European Union and “zero”

for not being a member or only being a candidate country. I will use the information I will

found on EU:s web portal about membership in the Union. Even if the country only was a

member state for part of the year, I have coded it as “member of the EU”.

4.4 Candidate Country

Also from Necks et al study, I analyze the relationship between being an EU candidate country

and the economic growth. Therefore, I have developed the fourth statement:

S4: Having a status as a candidate country is correlated with an increased GDP growth.

When I analysis the relationship, I will use a dummy variable and code “one” for being an EU

candidate country and “zero” for not being a candidate country or being a member of EU. Also

39

Freedom House Analysis Freedom in the World Methology 40

Developed by Mckibben and Sachs, 1991 41

Neck et al 2000:71-82

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here, I will use the information I have found on EU:s web portal about which states that have

status as a candidate country. Even if the country only was as candidate country for part of the

year, I have coded it as “candidate country”.

4.5 Export Ratio of GDP

Chan and Dang have analyzed the relationship between the post-war liberalization of world

trade and the increase in the world GDP per worker. They have used data from the Penn World

Table and analyzed the GDP for 50 countries between 1950 and 2000 and for 98 countries

between 1970 and 2000 and analyzed the relationship between the countries import, export, and

the participation in WATT and the membership in WTO and the GDP per capita. Their

conclusion was that it was a positive relationship between trade and economic growth.42

From

Chan’s and Dang’s theory about trade-liberation and economic growth, I have developed the

fifth statement:

S5: A high export ratio of GDP is correlated with an increased GDP growth.

When answering the hypothesis, I will investigate the relationship between the export and the

GDP. I will measure the export as ratio of GDP by using the statistic from the World Bank

about the export ratio of the economy as whole.

4.6 Import Ratio of GDP

From Chans and Dangs study, I will analyze the relationship between the import and the GDP.

My sixth statement will be:

S6: A high import ratio of GDP is correlated with an increased GDP growth.

I will measure the import as ratio of GDP and I will use the statistic from the World Bank about

the import ratio of the economy as whole.

4.7 Military Expenditure

Cappelin, Gleditsch and Bjerkholt have studied 17 OECD countries for the period 1960-1980

and analyzed the relationship between military expenditure and economic growth. They

analyzed how military expenditure affected the manufacturing output, the investment and the

42

Chan and Dang 2009:689-703

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economic growth and concluded that high military expenditure had a positive impact of

manufacturing output and a negative effect on investment. The net effect was negative on the

economic growth, except for the Mediterranean countries.43

From this study, I have developed

my seventh statement:

S7: A low military expenditure ratio of GDP is correlated with an increased GDP growth.

According to Cappelin et al, only the Mediterranean countries did not show any relationship

between high military expenditure and low economic growth. But Spain during the sixties and

Croatia during the year 2000 is not so similar, thou I will argue that the states of ex-Yugoslavia

would have more similarities with the rest of the OECD countries in the study. I will use data

from the World Bank and measure the expenditure in percent of GDP (0-1).

4.8 Internet access

Kenny had analyzed the impact on internet access for the economic growth in the less-

developed countries in the world. The result shows some positive impact in theory, but in

practice, the barriers are many. In many pour countries, most of the people are to pour to have

access to internet. In many less-developed countries, when a lot of people do not speak English,

the use of Internet usage goes down. Kenny has also analyzed US and other wealthier OECD

countries and found some positive impact.44

From this analysis, I have developed my eighth

statement:

S8: A high proportion of internet access is correlated with an increased GDP growth.

Since the Balkan countries are somewhere between less-developed and wealthy countries, I

have developed S8 to test if any correlation exist. I will use the data from the World Bank.

4.9 Conflicts or Intrastate Wars

Collier has analyzed the impact of civil war and its effect on economic growth. According to

him, civil war affects the economic growth in a country more than international war, since it

undermines the trust for the state. Through a regression analyze, Collier has analyzed the data

from Penn World Tables (BNP) and the relationship between the standard source on civil wars

43

Cappelin, Gleditsch and Bjerkholt 1984:361-373 44

Kenny 2003:99-113

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from Small and Singer, (1982 and 1994). He concludes that during civil war, the GDP per

capita declines at an annual rate of 2,2 percent.45

From Collier’s statement that conflicts and

intrastate wars lead to less economic development, I have developed my ninth statement:

S9: The absence of conflicts or intrastate wars is correlated with an increased GDP growth.

When measuring this variable, I will measure the occurrence of intrastate war in the countries. I

will code the occurrence as a dummy variable where zero corresponds to not being in a civil

war and one corresponds to being in a civil war. I will mainly use A Revised List of Wars

Between and Within Independent States, 1816-2002 by Kristian Skrede Gleditsch to code the

variable as “within” or “not within” a intrastate war. Between 2002 and 2006, I will use the

Encyclopedia Britannica Online to code the variables. I will count every conflict within the

SFRY as an intrastate war.

4.10 Inflation

Barro has analyzed 100 countries between 1960 and 1990 to investigate the relationship

between inflation and economic development. According to him, an increase of the inflation by

10 percent leads to decrease of the GDP per capita by 0,2-0,3 percent on average. The result is

only statistically significant when high-inflation states are included in the sample.46

From

Barro’s theory about the impact of low inflation, I have developed the tenth statement:

S10: A low inflation is correlated with an increased GDP growth.

When measure this variable, I will measure the inflation in the countries as percent (0 to 1). I

will test this statement on the Balkan countries and see if the inflation rate has mattered. I will

use the inflation rate that I will find on the World Bank web page.

4.11 Year

I will also use a variable to measure if the fact that “the times running” have any impact on the

economic growth. Perhaps all countries are getting wealthier? I will code this variable as 1991-

2008, since this is the time range I will study. My statement will be:

45

Collier 1999:168-83 46

Barro 1995:1-36

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S11: For every year which has past, the GDP will grow more and more.

3.12 Population

I will also use a variable to measure if the size of the population will have any impact on the

economic growth. Does the economy in a country correspond to “economic of scale” or

“diseconomic on scale”? Or constant return to scale? I will measure the population between

100 000 and 10 000 000. I will use the data from the World Bank. My statement will be:

S12: A bigger population is correlated with an increased GDP growth.

In Table III, I will summarize how I will code the variables.

Table III: Summary of how to Code the Variables

Variable Code

Political Rights 1-7

Civil Liberty 1-7

European Union 0 = not being a member of the European Union

1 = being a member of the European Union

Candidate Country 0 = not having the status as a Candidate Country

1 = having the status as a Candidate Country

Export ratio of GDP 0-1

Import ratio of GDP 0-1

Military expenditure ratio of GDP 0-1

Internet Access 0-1

Conflict or Intrastate War 0 = not being in a Conflict or Intrastate war

1 = being in a Conflict or Intrastate war

Inflation 0-1

Year 1991-2008

Population 100 000 -10 000 000

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5 The GDP Growth and GDP per Capita

When I analyze the economic growth for the states, I will use the data from the World Bank.

From their homepage, I will find statistic over the economic growth for the states. Some of the

scientists and economics I base my statements on have used GNP or GNP when they measure

the economy, but in my study, I will only use the term GDP.

Since I will use the World Bank as my source, I will use their definition of economic

growth or GDP growth. The annual percentage growth rates of GDP as market prices are based

on constant local currency. The aggregates are based on constant 2000 US-dollar. The single

year official exchange rate is used when the Dollar figures for GDP are converted from

domestic currencies. The GDP is the sum of gross value added by all resident producers in the

economy and all product taxes. Any substitute not included in the value of the products is not

included in the GDP. Depletion, degradations of natural resources or deduction for

depreciations of fabricated assets is not calculated in GDP.47

After the analyses of the correlation between GDP Growth and the variables, I will analyze the

correlation between the GDP per Capita and the variables. Also this data is from the World

Bank. Since the World Bank does not show the GDP per Capita, I have counted is from the

GDP and the population size.

47

World Bank: Indikators

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6 Limitations

I have only included some possible variables. In this section, I will discuss some other ones

and why I have excluded them.

Alberto Alesina et al have made a study about the relation between ethnic, religious and

linguistic fractionalization and the economic development in 190 countries. They have

developed a fractionalization index which reflected the probability that two randomly selected

individuals from a population belonged to different groups48

. The results are divided, but they

conclude that the ethnic and linguistic fractionalization variables are likely to increase the GDP

growth and the quality of policies and institutions49

. First, I wanted to include this variable as

well, but since I only have dates for one year for each country, I decide to not include that in

my study.

There is a lot of studied about tourism and economic development. One example is

Ateljevic and Milne, which have analyzed tourism and its impact on economic growth.

According to them, tourism is a major global economic force. Further, tourism gives shape to

the land and provides job and income to the locals. Tourism also produces representation and

social, cultural and psychological meanings to a place, which in turn increase and reproduce its

value. Finally, Ateljevic and Milne conclude, the tourism helps to increase the economic

development in a country.50

I wanted to include the grade of tourism in my study, but since I

did not found any data for the grade of tourism, I had to exclude that as well.

Other possible variables I wanted to include are incomes difference, ratio of girls to boys

in school, illiteracy and ratio of urban living to rural living. The list can be long. The main

reason for my limitations is the data availability. Of course, I wanted to analyze “everything”

but since both the time and the data availability are limited, I have decided to choose ten

variables, which I hold for being important and where I had data for most of the years.

I know that I could not know for sure if my developed variables affect the economic growth or

on the contrary, but since I have support for my hypothesis through earlier research, I expect

that the variables affect economic growth. But I will keep that in the back head and scrutinize

my result critical.

48

The most famous and well-known index is called ELF (ethno linguistic fractionalization) and published in the Atlas Narodov Mira in 1964. 49

Alesina et al 2002:1-70 50

Ateljevic and Milne 2001:369.393

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7 Result

In this part, I will discuss the result from the Regression Analyses. I will start with a

Correlation Matrix, to determine if any of the variables is correlated with each other. Then I

will continue with some regression analyses for GDP Growth and GDP per Capita

7.1 Correlation Matrix: Independent Variables

Table IV: Correlation Matrix for the Independent Variables

Political

rights

Civil

Liberty

European

Union

Candidate

Country

Export

ratio

Import

ratio

Military

Expenditure

Internet

access Conflicts Inflation Year Pop.

Political rights

1

Civil Liberty

0,8576 1

European Union

-0,3876 -0,4813 1

Candidate Country

-0,5659 -0,5465 0,9313 1

Export ratio

0,0938 0,1562 0,0133 -0,0388 1

Import ratio

0,0478 0,0065 0,2121 0,154 -0,1607 1

Military

Expenditure

0,526 0,6253 -0,1538 -0,3504 0,8 -0,4129 1

Internet access

-0,3167 -0,448 0,3669 0,4321 -0,1002 0,4252 -0,4444 1

Conflicts

0,2767 0,3565 -0,0624 0,1595 -0,0295 -0,2418 0,7747 -0,2815 1

Inflation

0,1014 0,1637 -0,02 -0,0442 -0,0113 -0,08 0,4687 -0,1686 0,6043 1

Year

0,0125 -0,2556 0,2112 0,3471 -0,0992 0,544 0,5159 0,705 -0,4201 -0,3022 1

Population

0,2291 0,0692 -0,1979 -0,2508 0,0406 -0,4661 0,3088 -0,135 0,1831 0,07595 0,1293 1

When studying table IV, one can see that Political Rights and Civil Liberties are correlated to

86 percent with each other. This is not a surprise, since political rights and civil liberties often

are walking hand-in-hand. A membership of the European Union and having a status as a

Candidate Country is also high correlated, but since most of the states nor is a member of the

European Union neither has a status as candidate country, I will argue that the correlation is

between not being a member and not having the status. The correlation between Conflicts and

Intrastate Wars and Military Expenditure is 77 percent. Perhaps not a surprise that conflicts

and wars lead to high military expenditure. Conflicts and Intrastate Wars is also correlated to

sixty percent with high inflation. The correlation between membership in the European Union

or being a Candidate Country is negatively correlated with Political Rights or Civil Liberty.

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Since a low score in both Political Rights and Civil Liberty indicate on a high degree of rights

and freedom, one has to disregard from the minus sign. Finally, Internet access is 71 percent

correlated to year, indicating that more and more people are using internet.

7.2 GDP Growth

Now, I will do a Multiple Regression Analysis with all the variables. Further, I will do a simple

regression Analysis for all variables one by one. In the cases where I find a correlation, I will

continue by additional multiple regression analysis.

7.2.1 GDP Growth: Multiple Regression Analysis

Table V: Multiple Regression Analysis where GDP Growth is the Dependent Variable

Coefficient

Regression

Standard Error p-value

Political rights -0,0070112 0,0066112 0,294

Civil Liberty -0,0027709 0,0096659 0,776

European Union -0,0016292 0,0157522 0,918

Candidate Country -0,0107007 0,0091886 0,250

Export ratio of GDP -0,0043327 0,0025978 0,102

Import ratio of GDP** 0,105749 0,0513846 0,045

Military Expenditure 0,0602065 0,3470837 0,865

Internet access -0,0181223 0,0273785 0,511

Conflicts or Intrastate Wars** 0,0474324 0,0235353 0,050

Inflation*** -0,0106008 0,0019345 0,000

Year 0,0015047 0,0017505 0,394

Population 2,86 x 10-9

2,99 x 10-9

0,344 *Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

When doing a multiple regression analysis with all variables, the impact of import and

intrastate wars are significant on the 5% level and the impact of inflation is significant on the

1% level. In this model, if the import ratio of GDP increase by one percent point, the GDP

growth will increase by 11,6 percent points. If the inflation increase by one percent point, the

GDP growth will decrease by 1,1 percent points and if there occur an conflict or intrastate war,

the GDP will increase by 4,7 percent points. It seems that it exist some bias, because that is not

probable that an intrastate war should increase the GDP growth.

The regression standard error is half as big as the coefficient for both import ratio and

intrastate war. For the inflation, the regression standard error is only twelve percent of the

coefficient. This is not a surprise, since the p-value is less than 0,001.

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In this analysis, the number of observations was 59 and the R2 is 0,5619, indicating that

the variation in the economic growth which could be explained in this model is 56,19 percent.

7.2.2 GDP Growth: Simple Regression

As you see in table VI, the only variables which are significant on any interesting level are the

import ratio of GDP, Conflicts or Intrastate Wars, Inflation and Year. Conflicts or Intrastate

Wars is the only one which is significant on the 1% level; the three others are significant on the

5% level.

The first four variables in the table have a p-value higher than 0,8. Export Ratio of GDP,

Military Expenditure, Internet Access and Population have a lower p-value, between 0,2 and

0,5, but still to high to be interesting in this analysis.

Table VI: Simple Regression Analysis where GDP Growth is the Dependent Variable

Coefficient

Regression

Standard Error p-value R2

Reg. 1 Political rights -0,001853 0,008833 0,834 0,0005

Reg. 2 Civil Liberty -0,002255 0,009687 0,816 0,0006

Reg. 3 European Union 0,01148 0,05901 0,846 0,0004

Reg. 4 Candidate Country 0,006028 0,03225 0,852 0,0004

Reg. 5 Export ratio -0,01299 0,01357 0,341 0,0105

Reg. 6 Import ratio 0,1966** 0,08898 0,030 0,0537

Reg. 7 Military Expenditure -0,4706 0,3684 0,206 0,0238

Reg. 8 Internet access -0,79845 0,07220 0,273 0,0179

Reg. 9 Conflicts -0,12773*** 0,03741 0,001 0,1093

Reg. 10 Inflation -0,01261** 0,005943 0,037 0,0503

Reg. 11 Year 0,05205** 0,002557 0,045 0,0418

Reg. 12 Population -3,71 x 10-9

5.82 x 10-9

0,525 0,0043

*Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

In Regression 1, where I analyzed the relationship between the import ratio of GDP and the

GDP-growth, the number of observations is 88. The R2 is 0,0537, indicating that the variation

in the economic growth which could be explained by the import ratio of GDP is 5,37 %. The

coefficient is 0,20, indicating that an increase in the import ratio of GDP by one percentage

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point will increase the GDP growth by 20 percent points. Further, the regression standard error

is 0,089, which is about half of the coefficient.

The p-value is 0,030, which make the result significant in the 5% level.

In Regression 9, where I analyzed the relationship between the occurrence of Conflicts or

Intrastate wars and the GDP-growth, the number of observations is 97. The R2 is 0,1093,

indicating that the variation in the economic growth which could be explained by the Conflicts

or Intrastate wars is 10,93 %.

The coefficient is -0,13, indicating that the occurrence of Conflicts or Intrastate wars will

decrease the GDP growth by 13 percent points. This is not that amazing, since a conflict or

intrastate war is costly for the state and does not contribute to the economic development. The

regression standard error is 0,037, which is about 28 percent of the coefficient. The p-value is

0,001, indicating that the result is significant on a 0,1% level.

In Regression 10, where I analyzed the relationship between Inflation and the GDP-growth, the

number of observations is 87. The R2 is 0,0503, indicating that the variation in the economic

growth which could be explained by the inflation is 5,03 percent.

The coefficient is -0,013, indicating that when the inflation increase by one percentage

point, the GDP growth will decrease by 1,3 percent points. The regression standard error is

0,0060, which is about half of the coefficient. The p-value is only 0,037.

In Regression 11, where I analyzed the relationship between Years and the GDP-growth, the

number of observations is 97. The R2 is 0,0418, indicating that the variation in the economic

growth which could be explained by the year is 4,183 percent. The coefficient is 0,0052,

indicating that for each year that past, the GDP growth will increase by 0,52 percent points.

The regression standard error is 0,0026, which is about half of the coefficient. The p-value is

0,045.

7.2.3 GDP Growth: Controlling for Variables

After this simple regression analysis, I will continue with some multiple regression analysis, to

determine if the correlation remains when controlling for other variables. I started with a couple

of multiple regression analysis where I controlled for the other variables. I controlled for all

twelve variables and the result can be found in Appendix I. In most cases, when controlling for

other variables, the result did not change dramatically. Therefore, I can conclude that these four

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variables (Import Ratio of GDP, Conflict and Intrastate War, Inflation and Year) are the ones

that mattered. To continue, I have done a couple of more multiple regression analyses that you

can find in table VII:

Table VII: Multiple Regression Analyses where GDP Growth is the Dependent Variable

Import Ratio Conflicts Inflation Year R2

Reg. 1 0,233111** -0,0790532 -0,0097472 -0,0024501 0,1265

0,0945352 0,0552171 0,006581 0,0031677

Reg. 2 0,1965883** 0,0537

0,0889776

Reg. 3 -0,1277334*** 0,1093

0,0374085

Reg. 4 -0,126135** 0,0503

0,0584932

Reg. 5 0,0052046** 0,0418

0,0025573

Reg. 6 0,2094343** -0,0885489* 0,0925

0,0879047 0,0,0464561

Reg. 7 0,2031074** -0,0114647* 0,1039

0,0913003 0,0058658

Reg. 8 0,1862464* 0,0014493 0,0569

0,091412 0,0027062

Reg. 9 -0,0483874 -0,103085 0,0603

0,0512206 0,0064281

Reg. 10 -0,120151*** 0,0009247 0,1102

0,0446738 0,0029444

Reg. 11 -0,0122281 0,0004238 0,0506

0,0065279 0,0028843

Reg. 12 0,215734** -0,062005 -0,0084416 0,12

0,0916017 0,0505032 0,0063452

Reg. 13 0,2208427** -0,1002361* -0,0013611 0,0946

0,0919735 0,0535684 0,003061

Reg. 14 0,02067388**

-0,01202227* -0,0006398 0,1044

0,09333148

0,0064269 0,0029229

Reg. 15 -0,0528115 -0,0107072 -0,0006703 0,0608

0,0554437 0,0067238 0,0031061 *Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

When doing a multiple regression analysis with all four variables (Regression 1), only the

impact of Import Ratio is significant on the 5% level. When doing a multiple regression

analysis with two variables, Import Ratio and Conflicts (Regression 6) and Import Ratio and

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Inflation (Regression 7) the result is significant for both variables in both combinations, but

none of the other combination between two variables (Regression 8-11) shows a significant

result for both.

When doing a multiple regression analysis between three variables (Regression 12-15),

we get approximately the same result. It seems that the variable year does not matter. Instead,

the variable is only correlated with the other variables. Since conflicts and Inflation is

correlated to 60 percent, it is possible that both can explain some of the GDP growth, but when

taking them into the same model, they cannot explain enough one by one.

As a conclusion, it seems that the GDP growth best could be explained by either Import

Ratio and Conflicts (Regression 6) or Import Ratio and Inflation (Regression 7). The equations

to determine the GDP growth will be:

Y = 0,2094Import Ratio -0,0879047Conflict - 0,06177 + ᵋ (1)

Y = 0,2031Import Ratio -0,01146Inflation - 0,05869 + ᵋ (2)

The constants are taken from the regression analyses. ᵋ is the error term.

In equation 1, The R2 is 9,25 percent and for equation 2, R

2 is 10,39 percent. In equation

1, when the Import Ratio of GDP increases by one unit, the GDP will increase by 0,21 unit.

Further, if the state is taking part in a conflict or intrastate war, the GDP growth will decrease

by 0,062 units. In equation 2, when the Import Ratio of GDP increases by one unit, the GDP

will increase by 0,20 unit. Further, when the inflation increases by one unit, the GDP growth

will decrease by 0,011 units.

7.3 GDP per Capita

Table VIII: Correlation Matrix between GDP per Capita and GDP Growth

GDP per Capita GDP Growth

GDP per Capita 1,0000

GDP Growth -0,0715 1,0000

As you can see in table VIII, GDP per Capita and GDP growth is not correlated to each other at

all. The explanation is that if GDP per Capita measures the income and the GDP growth

measures the derivate of the income.

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7.3.1 GDP per Capita: Simple Regression Analysis

Table IX: Simple Regression Analysis where GDP per Capita is the Dependent Variable

Coefficient Standard Error p-values R2

Reg. 1 Political rights -2847,077*** 277,8637 0,000 0,5468

Reg. 2 Civil Liberty -2841,255*** 341,179 0,000 0,4436

Reg. 3 European Union 16380,35*** 4521,751 0,000 0,5275

Reg. 4 Candidate Country 8834,38*** 916,557 0,000 0,5079

Reg. 5 Export ratio of GDP 405,504 515,0011 0,433 0,0069

Reg. 6 Import ratio of GDP -303,6235 3390,609 0,929 0,0001

Reg. 7 Military Expenditure -91216,58*** 27394,53 0,001 0,142

Reg. 8 Internet access 17238*** 2907,089 0,000 0,3442

Reg. 9 Conflicts or Intrastate Wars -2669,706 1891 0,162 0,0216

Reg. 10 Inflation -290,9652 257,5331 0,262 0,0146

Reg. 11 Year 339,2971*** 103,0865 0,001 0,1014

Reg. 12 Population -0,0004319 0,0002656 0,107 0,0285 *Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

As you can see in Table IX, when doing a Simple Regression Analysis, the result became

completely different from the analysis with GDP Growth. The variables which show a

significant result on the 1% level are Political Rights (Regression 1), Civil Liberty (Regression

2), European Union (Regression 3), Candidate Country (Regression 4), Military Expenditure

(Regression 7), Internet Access (Regression 8) and Year (Regression 11).

7.3.2 GDP per Capita: Multiple Regression Analysis

Table X: Multiple Regression Analysis where GDP per Capita is the Dependent Variable

Coefficient Standard Error p-value

Political rights -217,114*** 643,034 0,001

Civil Liberty -287,1847 883,9098 0,747

European Union 6973,766*** 1502,763 0,000

Candidate Country 1914,08** 832,2528 0,026

Export ratio of GDP 291,3001 254,1058 0,257

Import ratio of GDP -4020,396 4336,948 0,359

Military Expenditure 37110,28 31932,09 0,251

Internet access 5835,217** 2517,728 0,025

Conflicts or Intrastate Wars -160,643 2308,477 0,945

Inflation 85,52171 188,5945 0,652

Year 32,59757 133,4981 0,808

Population -53250,8 266133,2 0,842 *Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

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I continued the study by doing a Multiple Regression Analysis (Table X) with all variables. In

this analysis, the variables Political Rights, European Union, Candidate Country and Internet

Access showed a significant result on either 1% or 5% level. After that, I will continue by

analyze the variables which have showed significant result. I decided to exclude the variables

Internet Access, since it is more probably is the GDP per Capita which has affected the Internet

Access than vice versa.

7.3.3 GDP per Capita: Controlling for Variables

Table XI: Multiple Regression Analysis where GDP per Capita is the Dependent Variable

Political rights Civil Liberty

European Union

Candidate Country

Military Expenditure Year R2

Reg. 1 -2448,28*** 711,9881 9942,602*** 2567,413*** 14206,4 95,82308 0,8234 650,00109 701,3996 1319,777 897,4609 18777,7 96,31265

Reg. 2 -1887,376*** 9713,318*** 2797,534*** 13799,5 51,2549 0,8294 342,4111 1300,619 18777,99 18778 85,74377

Reg. 3 -1617,567*** 10033,12*** 3358,611*** 0,8273 212,7705 1150,847 712,895

Reg. 4 11435,01*** 5975,628*** 0,7118 144,041 792,0264

*Significant on 10% level, **Significant on 5% level, ***Significant on 1% level

As you see in Regression 1 in Table XI, when doing a multiple regression analysis with all six

variables, Civil Liberty is not significant. It is probably because the Civil Liberty is high

correlated with Political Rights. Further, Military expenditure and Year show no significance in

Regression 1 or 2. When making a multiple regression analysis between Political Rights,

European Union and Candidate Country (Regression 3), all three variables shows a significance

on the 1% level and the R2 indicate that the model can explain 82,73 percent of the variance.

The equation for the GDP per Capita is:

Y = -1617Political Rights + 10033EU + 3358Candidate Country + 9127 + ᵋ (3)

The constant is taken from the regression analysis. The equation tell us that when the country

score one unit less on the Political Rights index (=is more democratic), the GDP per Capita will

increase by 1617 US-dollar. Further, if the country is a member of the European Union, the

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GDP per Capita will increase by 10033 US-dollar and if the country has a status as a candidate

country, the GDP per Capita will increase by 9129 US-dollar.

It seems that the democratization and the European Union have had an impact of the GDP per

capita. One problem with the impact of European Union and/or the status as Candidate Country

is that only Slovenia is a member and only Slovenia, Croatia and Macedonia have/have had a

status as candidate country. According to that, we cannot exclude that country specific qualities

have affected the result. Further, since the European Union has a stable economy as a requisite

for its member states, we cannot exclude that is the high GDP per capita that has affected the

membership and/or the status.

As a summary, since it seems that the democratization and the Europeanization had mattered

for the GDP per Capita. I would conclude that the globalization has had a positive impact on

the GDP per Capita for the countries in the Balkan Peninsula.

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8 Summary and Conclusion

Since the dissolution of the Socialist Federal Republic of Yugoslavia, all countries in the

Balkan Peninsula have experienced an increased economic growth. The closed Plan Economy

which existed during the Communist time has only led to a decline in the economy. On the

other hand, the more open Socialist Self-Management System that comes after has led to an

increased economic growth. During the last two decades, the growths for the countries have on

average been positive, but the growth has differed, between both countries and times. It seems

that the countries that had the highest GDP per Capita in the early nineties also is the countries

which experienced the lowest GDP Growth and vice versa. The general explanation could be

the Catch Up effect, denoting that a poor country has a higher economic growth compared to a

rich country and in the long run, the GDP per Capita will be equal for all countries.

When analyzing the correlation between GDP Growth and the independent variables, two

combinations give us a significant result: Import Ratio and Conflicts or Intrastate Wars or

Import Ratio and Inflation. The analyses tell us that having a high Import Ratio and not being

in an Intrastate War or having a high Import Ratio and having a low Inflation is god for the

economic growth. It is surprising that Import Ratio has a positive impact where Export Ratio

has not. Perhaps there exists a bias or a variable which is negatively correlated with Export

Ratio.

When analyzing the correlation between GDP per Capita and the independent variables,

the results are totally different: the combination Political Rights, European Union and

Candidate Country gives us a significant result. The result tell us that having a high degree of

political rights (=score low in the Freedom House index) and being a member of the European

Union or having a status as a Candidate Country is associated with a higher GDP per Capita. Of

course, a country could not be both a member of the European Union and have a status as a

Candidate Country at the same time, but both variables will be associated with a higher GDP

per Capita.

The two dependent variables GDP growth and GDP per Capita is low correlated with

each other and are associated with totally different variables. Since the GDP growth shows the

difference in GDP and measures in percent, where GDP per Capita shows the income per

person and measure in US-dollar, this is not a surprise. Even if one of the countries has the

highest GDP in relation to the other for two years, the GDP growth could still be zero if the

country did not increase its GDP between the two years.

Since the European Union has both a stable economy and a high degree of democracy as

a requirement, it is possible that both a high GDP per Capita and a high degree of Political

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Rights affect the membership of the Union/the status as a Candidate Country. On the other

hand, a membership in the Union can be the carrot for the countries and influence them to

increase their GDP and implement Political Rights. The only country which is a member of the

European Union, Slovenia also has the highest GDP per Capita on average. Further, the country

with the second highest GDP per Capita is Croatia, one of the two countries which have a status

as a Candidate Country.

If the catch up effect is true for the countries from the SFRY, it is not a surprise that the

variables which are associated with high GDP per Capita is not the one which is associated

with a high GDP Growth and vice versa. It is possible that a high GDP Growth is correlated

with a low GDP per Capita, but I have not done any analysis on that.

I would not generalize all of this result to all countries in the world, but since most of the

Countries in Eastern Europe which experienced centralized Plan Economy have had a very low

or negative GDP growth, I am sure that a more open economy would generate a higher GDP

Growth in most parts of the Eastern Europe.

As a conclusion, it seems that a high Import Ratio, a low Inflation and not being in a Conflict

or Intrastate War is most important for the GDP Growth for the countries from ex-Yugoslavia.

So my last advice to the Balkan Peninsula is:

Stay away from wars,

Do a lot of trade,

And try to keep your inflation low!

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Appendix I: Multiple Regression Analyses between GDP Growth and Significant Variables

For all tables in Appendix 1: *Significant on 10% level, **Significant on 5% level, ***Significant

on 1% level

Table XII: Multiple Regression Analyses between GDP Growth, Import Ratio and other variables

Import ratio

Political

rights

Civil

Liberty

European

Union

Candidate

Country

Export

ratio

Military

Expenditure

Internet

access Conflicts Inflation Year Population

0,1965883**

Reg. 1 0,889776

0,1781417* 0,0136 0,002

Reg. 4 0,0922046 0,02078 0,0233

0,2004245** -0,0029 -0,0132

Reg.3 0,0907028 0,06821 0,o343929

0,1917804** -0,011151

Reg. 5 0,0893175 0,013319

-0,0057374 -0,48958

Reg. 6 0,0772772 0,414163

0,3587504*** -0,10874

Reg. 7 0,0991886 0,06912

0,2094343** 0,0879047*

Reg. 8 0,0879047 0,051477

0,2031074** -0,0879*

Reg. 9 0,0913003 0,00587

0,1862464* 0,09141

Reg. 10 0,091412 0,00271

0,2067388* -0,012 -0,0006

Reg. 11 0,0933148 0,00643 0,00292

0,233111** -0,790532 -0,00975 -0,0025

Reg. 12 0,0945352 0,055217 0,00658 0,00317

0,2665147***

1,21x10 -8**

Reg. 13 0,0963155 6,80x10 -9

0,2602803** 0,00064 1,18x10 -9*

Reg. 14 0,10004044 0,00272 6,94x10 -9

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Table XIII: Multiple Regression Analyses between GDP Growth, Conflicts and other variables

Conflicts

Political

rights

Civil

Liberty

European

Union

Candidate

Country

Import

ratio

Export

ratio

Military

Expenditure

Internet

access Inflation Year Population

-0,374086***

Reg. 1 0,0549918

-0,1565927** -0,005652 0,020364

Reg. 2 0,041886 0,020568 0,023304

-0,1311233** 0,00814 -0,016442

Reg.. 3 0,0384743 0,063235 0,0350764

-0,0880355* 0,204695** -0,010819

Reg. 4 0,0465481 0,088258 0,0131225

-0,0721338

0,09113

Reg. 5 0,0526908

0,54988

-0,0687298 -0,09755

Reg. 6 0,0678386 0,074266

-0,0592902 -0,01069 -0,00099 4,98x10-9

Reg. 7 0,0562738 0,006742 0,003144 6,71x10-9

-0,0483874 -0,10309

Reg. 8 0,0512206 0,006428

-0,120151*** 0,000925

Reg. 9 0,0446738 0,002944

-0,134202*** 2,86x10-9

Reg. 10 0,0398312 5,86x10-9

-0,0790532 0,23311** -0,00975 -0,00245

Reg. 11 0,0552171 0,094535 0,006581 0,003168

-0,1116426** 0,33664*** -0,00439 -0,00439 1,57x10-8

Reg. 12 0,0560492 0,104047 0,006438 0,003224 7,22x10-9

-0,1116426** 0,33664*** -0,00439 -0,00439 1,57x10-8

Reg. 13 0,0560492 0,104047 0,006438 0,003224 7,22x10-9

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Table XIV: Multiple Regression Analyses between GDP Growth, Inflation and other variables

Inflation

Political

rights

Civil

Liberty

European

Union

Candidate

Country Import ratio

Export

ratio

Military

Expenditure

Internet

access Conflicts Year Population

-0,0126135**

Reg. 1 0,00659433

-0,0142424** 0,00286 0,019181

Reg. 4 0,0060631 0,02098 0,034018

-0,0128706** 0,00815 -0,016071

Reg.3 0,0060334 0,0627 0,034809

-0,0114647*' 0,2031074**'

Reg. 5 0,0058658 0,0913

-0,0126243**

-0,01282

Reg. 6 0,0059816

0,013452

-0,0084295 0,04282 -0,04792

Reg. 7 0,0057612 0,552397 0,016334

-0,0114242 -0,09425

Reg. 8 0,0076969 0,072211

-0,0123687* 0,000281 3,89x10-9

Reg. 9 0,0065573 0,002906 6,63x10-9

-0,0097472 0,233111** -0,07905 -0,00245

Reg. 10 0,006581 0,094535 0,055217 0,003168

Table XIV: Multiple Regression Analyses between GDP Growth, Year and other variables

Year

Political

rights

Civil

Liberty

European

Union

Candidate

Country Import ratio

Export

ratio

Military

Expenditure

Internet

access Conflicts Inflation Population

0,0052046**

Reg. 1 0,002263841

0,0070224** -90,0163 0,026904

Reg. 4 0,0032178 0,022752 0,027104

0,006176** -0,00462 -0,02599

Reg.3 0,0028733 0,06573 0,038401

0,0013591 0,12821998* -0,01088

Reg. 5 0,0027139

0,091731 0,013389

-0,0114242 -0,09425

Reg. 6 0,00676969 0,072221

0,0022843

0,301378 -0,006747

Reg. 7 0,0021208

0,052805 0,052805

0,0002812 -0,012359' 3,89x10-9

Reg. 8 0,0029058 0,006557 6,63x10-9

0,0004238 -0,01223

Reg. 9 0,0028843 0,006528

-0,0024501 0,233111** -0,079053 -0,00975

Reg. 10 0,0031677 0,094535 0,055217 0,006581

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