The Balkan Countries in the Process of European Integration: Is there a Convergence Process?

Abstract

Balkan countries have been rapidly changing since 1990's. In spite of some Balkancountries (such as Turkey and Greece) were relatively stable in 1990s, there was warin Serbia, Montenegro, Croatia, Bosnia-Herzegovina, and Macedonia. Some formersocialist countries (Bulgaria, Slovenia and Romania) and Greece became full memberof EU, after the rugged process. The others have been struggling for this aim. In this process, all Balkan countries have some political, economic and social challenges. The aim of this paper is to investigate whether or not economic convergence among Balkan countries in the process of European Integration in the period of 1997-2007. Totest convergence, we use approach of Barro and Sala-i Martin. Our study indicates that there is no convergence among Balkan countries in the process of European Integration in the period of 1997-2007.

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Fatih ÇELEBİOĞLU (Ph.D)
Dumlupınar University, Faculty of Economics
and Administrative Sciences,
Department of Economics, Kütahya, TURKEY
Hüseyin ALTAY (Ph.D)
Bilecik University, Faculty of Economics
and Administrative Sciences,
Department of Economics
The Balkan Countries in the Process of European Integration:
Is there a Convergence Process?
Abstract
Balkan countries have been rapidly changing since 1990’s. In spite of some Balkan
countries (such as Turkey and Greece) were relatively stable in 1990s, there was war
in Serbia, Montenegro, Croatia, Bosnia-Herzegovina, and Macedonia. Some former
socialist countries (Bulgaria, Slovenia and Romania) and Greece became full member
of EU, after the rugged process. The others have been struggling for this aim. In this
process, all Balkan countries have some political, economic and social challenges. The
aim of this paper is to investigate whether or not economic convergence among
Balkan countries in the process of European Integration in the period of 1997-2007. To
test convergence, we use approach of Barro and Sala-i Martin. Our study indicates
that there is no convergence among Balkan countries in the process of European
Integration in the period of 1997-2007.
Key words: Balkan Countries, European Integration, Convergence,
Divergence.
Introduction
Balkan countries have been rapidly changing since 1990’s. In spite of some Balkan
countries (such as Turkey and Greece) were relatively stable in 1990s, there was war
in Serbia, Montenegro, Croatia, Bosnia Herzegovina, and Macedonia. Some former
socialist countries (Bulgaria, Slovenia and Romania) and Greece became full member
of EU, after the rugged process. The others have been struggling for this aim. In this
process, all Balkan countries have some political, economic and social challenges. We
are interest in economic challenges about Balkan countries, especially deal with level
of per capita income of these countries in this study.

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Mostly Balkan countries have low per capita GDP (Gross Domestic Product). For
example Albania has $1677 per capita GDP in 2007; Bosnia and Herzegovina has
$2044; Bulgaria has $2401; Macedonia has $2061; Montenegro has $2269; Romania
has $2595 and Serbia has $1780. Exclusively Greece ($15052), Croatia ($5794),
Slovenia ($13333) and Turkey ($5053) have relatively bigger than aforementioned
countries’ per capita GDP. It is normally expected that EU (European Union)
membership process support to improving per capita GDP. In the next stages, we
search this expectation about Balkan countries.
This paper is organized as follows: the next section describes concept of convergence.
Section 3 explains literatures about convergence. Section 4 introduces the data set.
Section 5 gives estimation results about beta (absolute and conditional) convergence
and sigma convergence. The last section provides some concluding remarks.
What is convergence?
Convergence concept is defined as poorer economies tend to grow at faster rates than
richer economies. According to this concept all economies should in the long run
converge in terms of per capita income and productivity. It is supposed that
developing countries have the potential to grow at a faster rate than developed
countries.
The issue of economic convergence at national and regional level has been worked by
a lot of researchers in recent years. There are two concepts of convergence as β-
convergence and δ convergence. The seminal articles of Barro and Sala-i-Martin (1991,
1992, and 1995) and Mankiw et al. (1992) and then numerous studies have
investigated β-convergence and δ-convergence between different countries and
regions.
β-convergence is being investigated in two parts. These are absolute β-convergence
and conditional β-convergence. If all economies are structurally identical and have
access to the same technology, they are characterized by the same steady state, and
differ only by their initial conditions. This is the hypothesis of absolute β-convergence.
The concept of conditional β-convergence is used when the assumption of similar
steady-states is relaxed. Note that if economies of countries have very different
steady states, this concept is compatible with a persistent high degree of inequality
among countries.
At the same time, there is β-convergence in a cross-section of economies if we find a
negative relation between the growth rate of income per capita and the initial level of
income. If poor economies (or regions) tend to grow faster than rich countries (or

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regions), there is absolute β-convergence. The concept of conditional β-convergence
is used when the assumption of similar steady-states is relaxed (Sala-i Martin 1996-a).
δ-convergence can be defined as follows: A group of economies (or regions/provinces)
are converging in the sense of δ if the dispersion of their real per capita GDP levels
tends to decrease over time. This form uses two different types of variables: Standard
deviation and the coefficient of variation of the log of per capita income (Rey and
Montouri 1999). The existence of β-convergence will tent to generate δ-convergence
(Sala-i Martin 1996-b). We can say that β-convergence is necessary but not enough for
δ-convergence.
Because of the aim of this study estimates whether existence of β-convergence, we
shows only details belong to β-convergence. β-convergence is represented as follows:
,
ln ln( )
,,
,
yit T yit it
yit
αβ ε

+

=++


where
,
yit
is the per capita income of country (or region/province)
i
at year
t
,
α
is
constant and
β
is coefficient. If β has negative sign, this situation shows
convergence. The growth rate between period t and t + T is the dependent variable
and the log of per capita income in the initial
t
period is the independent variable.
Estimating β<0 from the above cited equation, we can conclude that less developed
economies show faster economic growth rate. Thus,
If β <0
0
0
y Absoluteconvergence
y Conditionalconvergence





= ⇒
≠⇒
According to absolute convergence concept, it is accepted that whole countries have
same conditions as technologic level, institutional structure and saving rate. But
conditional convergence approach includes new variables (for example, in our study:
urban population as % of total, foreign direct investment net inflows as % of GDP) that
reflect differences between economies.
We examine conditional convergence and explanatory variables are inserted on the
right hand side of the equation (1). We investigate the period of 1995-2001 following
the empirical works of Barro and Sala-i-Martin (1991, 1992, and 1995) and we use
equation (2):

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0 1 (,) 2 (,)
,
ln ln( )
,,
,
it it
yit T yUF
it it
yit
αβ β β ε

+

=+ +++


where
(,)it
U
is the urban population (as % of total) in the country i at year t,
(,)it
F
is the
foreign direct investment (FDI) net inflows (% of GDP) in country i at year t.
Literature
Chatterji (1992) showed that there are two mutually exclusive convergence clubs—
one for the 'rich' and one for the 'poor' where the division between rich and poor is
endogenously determined. Neven and Gouyette (1995) estimated convergence in
output per head across regions in the European Community, for the period 1975-
1990. Their study indicates that the distinction between the north and the south of
the European Community is likely to be more relevant in the analysis of growth
patterns than the distinction between the centre and the periphery. Furthermore the
population of the southern regions responds much more slowly to wage and
unemployment differences.
Quah (1996) occur that geographical factors are found to matter more than national –
macro ones; but both are important for explaining inequality dynamics in regional
convergence process of Europe. Barro et al. (1995) found that samples of open
economies, such as the US states, converge only slightly faster than samples of more
closed economies, such as the OECD countries. Bernard and Jones (1996) investigated
the sources of aggregate labor productivity movements and convergence in the U.S.
states from 1963 to 1989. Carlino and Mills (1996) obtained evidence for convergence
for the U.S. states and regions during the 1929 to 1990 period after allowing for a
break in the rate at which the various states and regions were converging in 1946. An
important finding of this research is that the US states and regions achieved per capita
earnings convergence by 1946. Chatterji and Dewhurst (1996) examined to test
whether the counties and regions are converging in terms of GDP per capita in
movements in the gross domestic product (GDP) per capita of English and Welsh
counties and Scottish regions for the period 1977 to 1991 and for six sub-periods.
Rey and Montouri (1999) provided new insights as to the throughout the system of
states, thereby complicating nature of regional income convergence patterns in the
transitional dynamics of the overall convergence US period 1929-1994. Their study
presented the first detailed evidence on the role of spatial effects in a regional income

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convergence study. Bazo et al. (1999) applied β and δ convergence approach to the
analysis of regional dynamics and convergence in the European Union (EU).
Soukiazis and Castro (2005) test convergence in living standards, productivity,
investment and unemployment among the European countries by using panel data
estimation techniques. Their study shows that the Maastricht rules and the Stability
and Growth Pact have not been as significant as the European authorities would
expect and even in cases where the Maastricht criteria had positive effects, these
were modest. Mora et al. (2005) offer an optimum definition of convergence clubs.
Their results show that European regions with high specialization in low-tech
industries in 1985 present non-significant conditional convergence, whereas regions
with lower specialization and situated further from the core experience higher rates.
Markandya et al. (2006) investigate the relationship between the energy intensity in
12 transition countries of Eastern Europe and that in the EU15 countries.
Le Gallo and Dall’erba (2006) suggested a general framework that allows testing
simultaneously for temporal heterogeneity, spatial heterogeneity and spatial
autocorrelation in β-convergence models and their study based on a sample of 145
European regions over the 1980-1999 periods. The estimation results indicate the
formation of a convergence club between the peripheral regions of the European
Union.
Ramajo et al. (2008) estimated that by using a spatial econometric perspective, the
speed of convergence for a sample of 163 regions of the European Union (EU) over
the period 1981–1996. Their estimations indicate that over the analyzed period, there
was a faster conditional convergence in relative income levels of the regions belonging
to Cohesion countries (5.3%) than in the rest of the regions of the EU (3.3%). Kocenda
et al. (2008) empirically examine the fiscal convergence of the recent ten European
Union (EU) members using the Maastricht fiscal convergence criteria. The findings
show poor fiscal performance in the European Union in general, suggesting that
monetary unions do not necessarily encourage fiscal convergence for its members.
Pfaffermayr (2009) contrasts the spatial Solow model and Verdoorn's model on
regional growth processes for 212 European regions covering the period 1980–2002.
Estimation results this investigation demonstrate that in both models the speed of
convergence also depends on the remoteness and the income gaps of all regions.
Descrıptıon of data set
Our dataset comes from the World Bank1 WDI (World Development Indicators)
Online. WDI (World Development Indicators) Online represents for each Balkan
country the level of per capita income over 1997-2007, urban population (as % of

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total) of the country in 1997 and foreign direct investment (FDI) net inflows (% of
GDP) of a country’s in 1997. This period that we use (1997-2007) is limited by data
availability. Our study includes Albania, Bosnia and Herzegovina, Bulgaria, Croatia,
Greece, Macedonia, Montenegro, Romania, Serbia, Slovenia, and Turkey. But Kosovo
is excluded in this study.
We select two variables (urban population and foreign direct investment) as
explanatory variables. In the integration process to market economy, many countries
are competing with each other to take more foreign direct investment. On the other
hand, after Socialist system, it is being waited that urban population is increase.
Empirical results
Beta Convergence
To test absolute β convergence, regressions are estimated between the rate of growth
of per capita income between 1997-2007 in the countries and the logarithm of their
initial (1997) level of per capita income. Table 1 shows summary of the absolute beta
convergence regression.
Table 1: Summary of the convergence regression (*) for the period of 1997-2007
1997-2007
Coefficient
-0.006
t-value
-1.262
R square
0.15
Significant
0.239
(*)Results are through OLS - SPSS
Empirical results indicate that the sign of β coefficient is negative, but it is statistically
not significant during the period of 1997-2007. It means that divergence process
stopped among Balkan Countries, however there is not any convergence process in
this period.
The urban population (as % of total) of the country in 1997 and foreign direct
investment (FDI) net inflows (% of GDP) of a country’s in 1997 have been used as
explanatory variables and introduced on the right hand side of the convergence
equation. Adding explanatory variables did not make any differences for the evidence
on convergence in regression 1 (see Table 2).

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Urban population (as % of total) has negative coefficients but it is very close to zero.
Foreign direct investment (FDI) net inflows (% of GDP) has positive coefficient.
Therefore, the results of conditional convergence analysis show the absence of
convergence between Balkan Countries.
Table 2: Convergence regressions (1997-2007) (*)
Regression 1
(Absolute Beta
Conv.)
Regression 2
(Conditional Beta Conv. with
explain. variables)
Constant
0.089
(0.043)
0.103
(0.037)
Log of initial per
capita
-0.006
(0.239)
-0.003
(0.547)
Urban
-0.0008
(0.174)
FDI
0.002
(0.397)
R square
0.150
0.381
(*) The significant values are in parentheses. Results are through OLS (Ordinary Least
Squares) – SPSS.
1 www.worldbank.org, The World Bank Group
Sigma Convergence
β-convergence is necessary but not enough for δ-convergence. In the results of
regression analysis, we haven’t found any evidence for β convergence (absolute or
conditional). These results have been also giving a signal for absence of δ convergence
in this period.
Standard deviation and variance is use to test whether or not sigma convergence.
Theoretically increasing of standard deviation over time is showing that exist of
divergence. If values of standard deviation are decreasing over time, there is
convergence process.
Table 3: Descriptive Statistics for per capita GDP in the period of 1997-2009(*)
Years
N
Mean
Std. Deviation
Variance
1997
11
3329.17
3290.66
10828461.73
1998
11
3437.94
3385.69
11462903.92
1999
11
3473.66
3538.36
12520021.03

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2000
11
3629.42
3685.08
13579871.53
2001
11
3719.46
3815.14
14555312.44
2002
11
3870.03
3955.10
15642863.96
2003
11
4028.48
4108.33
16878385.23
2004
11
4240.27
4265.95
18198412.99
2005
11
4432.07
4414.71
19489720.31
2006
11
4664.83
4598.64
21147541.93
2007
11
4914.78
4794.05
22982945.93
(*)Results are through SPSS.
Standard deviation value is (3290) in initial year, but its value is (4794) in the last year.
According to Table 3, the values of standard deviation are increasing over time.
Consequently there is divergence process in this period. We obtain similar results with
beta convergence in Table 3 and Figure 1.
In addition to this, Figure 2 shows the values of variance that coherent result with
standard deviation. It also shows divergence.
Figure 1: Standard Deviation in the period of 1997-2007
Figure 2: Variance in the period of 1997-2007
Standard Deviation
0
1000
2000
3000
4000
5000
6000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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Concluding remarks
The main purpose of this study was to find whether or not convergence process
among Balkan Countries in the process of European Integration in the period of 1997-
2007.
Our results indicated that the sign of β coefficient was negative, but it was statistically
not significant during the period of 1997-2007. According to these results, divergence
process stopped among Balkan Countries, however there was not any absolute
convergence process in this period. The results of conditional convergence analysis
showed the absence of convergence among Balkan Countries.
Besides the values of standard deviation are increasing over time. For this reason, we
stated that there was divergence process in this period.
Consequently, we found that EU membership process hasn’t been positively affecting
Balkan countries in terms of improvement of per capita GDP for the period of 1997-
2007.
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Variance
0
5000000
10000000
15000000
20000000
25000000
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

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