Download Democracy, Economic Freedom and Growth in Transition Economies

KYKLOS, Vol. 65 – August 2012 – No. 3, 371–407
Democracy, Economic Freedom and Growth in
Transition Economies
Evgeni Peev and Dennis C. Mueller*
I. INTRODUCTION
It has been roughly twenty years since communism collapsed in East Europe and
the Soviet Union. Although former communist countries are still generally
referred to as transition countries, enough time has elapsed since the end of
communism to claim that the transition process is, or should be, largely completed, and to assess how well the countries have done achieving growth and
transforming themselves into market economies.
When communism collapsed, the expectation (hope) in the West was that the
former communist countries would become both free market economies and
democracies. In many cases this happened, but not in all. Indeed, several former
members of the Soviet Union have either not adopted democratic institutions at
all, or quickly reverted to some form of authoritarian rule after a brief interlude
of democracy. In principle, a country might remain a dictatorship and still
introduce economic reforms that create market and capitalist institutions. Indeed,
since it faces no political opposition, a dictatorship might conceivably be able to
implement market reforms faster than a democracy. Singapore illustrates that
dictatorship and free market institutions can exist side-by-side. Singapore seems
to be somewhat of an exception, however. We shall, therefore, examine the extent
to which the introduction of democratic institutions has been accompanied by
market reforms and has led to more rapid growth in transition countries.
A large literature in political science links democracy to various socioeconomic variables like income and education. Kitschelt (1999) has argued that
institutional choices in the early post-communist transition years were the result
*
Evgeni Peev Department of Economics, University of Vienna, BWZ-Bruenner str. 72, A-1210 Vienna,
Austria. E-mail: [email protected] Tel: +43-1-4277-37489 and fax: +43-1-4277-37498. Dennis
C. Mueller Department of Economics, University of Vienna, Hohenstaufengasse 9, A-1010 Vienna,
Austria. E-mail: [email protected] Tel: +43-1-4277-37408 and fax: +43-1-4277-37498. The
authors would like to thank the editors of Kyklos, and the referees for helpful comments on the first draft.
We are grateful to participants at the DEMO workshop at Universitat Autònoma de Barcelona and
EAIRE 36th Annual Conference in Ljubljana. We wish to thank the Austrian National Bank for financial
support under the Jubiläumsfondsproject Nr. 12325 and the FWF project P 19522-G14.
© 2012 Blackwell Publishing Ltd., 9600 Garsington Road,
Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA
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EVGENI PEEV/DENNIS C. MUELLER
of “deeper” structural factors such as bureaucratic legacies and state-society
relationships. An additional factor spurring the movement toward democracy for
many transition countries was the lure of joining the European Union (Cameron,
2007). We identify the factors that led some former communist countries to
democratize and others not to do so.
When the transition process began, the state was the major economic actor in
all transition countries. State-owned enterprises were dominant, and the allocation of resources was guided by state bureaucracies rather than market forces.
Public sectors, measured by government outlays and taxes, were not unusually
high, however. The transition process thus has at least two dimensions with
respect to state activity: (1) privatization of state enterprises and the liberalization of economic activity, and (2) changes in government expenditures, transfers
and taxes. We treat both dimensions separately and propose and test hypotheses
about the relationship between democracy, economic liberalization and growth,
and between democracy, the size of the state, and growth.
A large literature has established a relationship between the quality of a
country’s economic institutions and economic growth.1 Countries with low
levels of corruption, strong property rights, independent judiciaries and other
institutions that underpin market systems grow faster. Glaeser, La Porta, Lopezde-Silanes and Shleifer (2004) have criticized this interpretation of the evidence,
however. They argue that economic and political institutions are endogenous,
and that the key exogenous determinants of economic growth are a country’s
stocks of human and social capital. The evidence that they present for this
proposition is drawn from the growth experiences of developing countries since
1960, and the long-run growth histories of currently, highly developed countries.
We reexamine the relationship between economic institutions and growth for a
sample of transition countries. Transition countries represent a particularly good
source of data for testing the importance of institutions for economic growth,
because they all began the transition process as dictatorships with weak economic institutions. Moreover, in comparison with other developing countries,
they all began the transition process with relatively large stocks of human capital.
Thus, differences in this variable should not play a decisive role explaining
differences in growth rates in the transition countries. In this article we test to see
whether the former communist countries, which did liberalize their economies,
were rewarded with faster growth.
Most studies of the effects of economic liberalization on growth measure
liberalization using a single index of economic freedom.2 Fidrmuc (2003), for
example, measures economic liberalization in transition countries using an
unweighted mean of eight EBRD indicators of progress in transition. This index
1.
See, Johnson, Kaufmann, and Shleifer (1997), Metelska-Szaniawska (2009) for transition countries, and
the survey by De Haan, Lundström and Sturm (2006).
2. There are few exceptions. See, Justesen (2008).
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
mixes different aspects of reform such as large- and small-scale privatization,
governance and enterprise restructuring, price liberalization, trade and foreignexchange liberalization, competition policy, and banking and securities markets
reform.3 As Heckelman and Stroup (2005) show, however, these aggregations
have several potential methodological problems. Therefore, in this article, we
examine the link between separate measures of liberalization and growth in
transition countries.
Some other authors have tried to overcome the aggregation problem by dividing the aggregate indexes into subsets. Tommaso, Raiser and Weeks (2007), for
example, subdivide them into one group of indexes measuring initial economic
reforms, and another containing indicators of institutional reform. However, as
the authors note, some aspects of reform (e.g. large-scale privatization) do not
clearly fall into either subset. Other authors examine the link between economic
reform and growth focusing on only a few dimensions of reform – small-scale
privatization, price and trade liberalization (Falcetti, Raiser and Sanfey, 2002);
privatization (Godoy and Stiglitz, 2006). A first contribution of the article is thus
to identify which economic freedoms make the greatest contributions to growth.
Several of the transition countries were hard hit by the global financial crisis
that occurred toward the end of the last decade. One of the interesting and,
perhaps for some, surprising findings of this article is that some of the factors
associated with faster growth prior to the crisis were associated with greater
declines in growth during the first years of the crisis. A second contribution of the
article is to examine the effects of economic freedoms, public expenditures and
fiscal balance on growth in transition countries over the period 1994–2007, and
following the financial crisis (2008–2009).
We wish to describe what has happened in the transition countries since the
end of communism and why it has happened. Underlying the analysis is the basic
premise that the shift to a market economy and the performance of the economy
were related to the strength of the democratic institutions established. We shall
see that this was largely the case with a few important exceptions.
The plan of the paper is as follows. We begin by describing what has happened
since the fall of communism (Section II). Which countries became democracies?
Which liberalized their economies? Which grew the fastest? In Section III we set
forward our main hypotheses and present some evidence regarding the adoption
of democratic institutions and economic freedoms in the transition countries.
The relationships between economic freedoms, the size of the state, and growth
are examined in Section IV. Additional tests of the main hypotheses are presented
in Section V. In Section VI, we analyze the experience of the transition countries
during the first years of the financial crisis (2008 and 2009). Conclusions are
drawn in the final section.
3.
Recently, EBRD constructed a ninth index measuring infrastructure reforms.
© 2012 Blackwell Publishing Ltd.
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EVGENI PEEV/DENNIS C. MUELLER
II. WHAT HAS HAPPENED?
1. Initial conditions
Table A1 lists for 1990 and 1995 the GDP per capita (Gcap) and secondary (Sec)
and tertiary (Ter) school enrollment percentages for each of the 24 transition
countries upon which this study focuses (see Appendix). The year 1990 comes
one year after the satellite communist countries in Europe abandoned communism, and one year before the Soviet Union did, and thus constitutes essentially
the starting point of the transition process. Because of the massive upheavals
through which the transition countries passed in the early years, the focus of this
study is on the post-1995 period, and thus, 1995 will also be used as a “starting
point” in our empirical work.
The last column in Table A1 presents the scores given by Kitschelt (1999,
Appendix) for the communist legacy (ComLeg) of each transition country. These
scores represent Kitschelt’s evaluation of the communist bureaucracies –
whether they were professional or relied on patronage, or patrimonial. The
higher the score, the better suited a country’s communist legacy was to the
development of liberal economic and democratic institutions.
Table A1 groups the transition countries into four sets: five central and
eastern European countries (CEE-5), five southern and eastern European countries (SEE-5), the three Baltic States, and the remaining countries from the
former Soviet Union (FSU).4 Each set of countries has elements of both geography and political history in common. The two richest transition countries in
CEE in 1990 were Slovenia and the Czech Republic. The three Baltic countries also had relatively high incomes per capita in the early 1990s. Russia,
Ukraine, Belarus, Turkmenistan and Kazakhstan had relatively high GDPs per
capita at the start of the transition, but the remaining FSU countries were
initially rather poor.
All transition countries had close to 100 percent school enrollments for
primary level students, so we focus on enrollments in secondary schools and
universities as measures of differences in human capital. Here the FSU countries
score rather well with the four lowest secondary school enrollments in 1990 in
the five SEE countries – Bulgaria, Croatia, Albania and Macedonia. Both Russia
and Belarus had over 50 percent enrollment levels at universities in 1990, the
only transition countries to reach such high levels. On the other hand, secondary
and tertiary enrollments tended to increase after the transition process began in
the CEE and SEE countries, while they tended to fall in most of the FSU
countries. Spagat (2003) establishes a link between the economic success of
4.
Some SEE countries (Bosnia, Kosovo, Montenegro and Serbia) and FSU countries (Uzbekistan) are not
included in our sample due to lack of data.
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
transition countries and their ability to maintain or increase their levels of human
capital.
The communist legacy scores for the four country groups are quite homogenous within groups, and differ greatly across groups. The five CEE countries
receive scores of 2 or in the case of the Czech Republic 3, and the three Baltic
States also get 2s. The five SEE countries get 1s, on the other hand (1.5 for
Croatia), while the FSU countries get either zeros (7) or ones (4). Thus, according to Kitschelt, the CEE and Baltic countries were much better positioned for a
successful transition than were the SEE and FSU countries.
2. Democracy
Of course, initial conditions for all transition countries with respect to politics
were essentially the same – authoritarian. Over time, however, some became
democracies while others remained or reverted back into dictatorship. To
measure the strength of a country’s democratic institutions, we use Freedom
House’s Index of Democracy. Freedom House has covered transition countries in
two publications: Freedom in the World reporting annually two indicators (political rights and civil liberties scores) and Nations in Transit, a comprehensive
survey of reforms in transition countries since 1994–95. While the former publication is useful for comparative studies between established democracies and
post-communist countries, the latter presents a more comprehensive picture of
post-communist transition focusing on seven dimensions of democratic institutions.5 We thus use this composite index of democracy in our study.6
The index runs from one to seven, with one signifying the strongest democratic institutions. The first three columns of Table A2 present the values for
1999, 2007 and the average for the period 1999–2007 (see Appendix).7 The
average for the CEE countries is around two. Thus, CEE countries score high in
terms of both levels of income per capita, and the strength of their democratic
institutions, which is consistent with the common finding in political science that
democracy and income levels are positively associated.8 The numbers in
Table A2 indicate that the five CEE countries have successfully introduced
democratic institutions, although they still do not match the scores of one
obtained by Western European, EU countries. Somewhat troubling is the slight
upward drift in the index in Poland and Hungary. Slovakia’s index, on the other
hand, fell over the time period bringing it more in line with the other CEE
5.
There is a very strong correlation between the average political rights and civil liberties score and the
composite index of democracy (in 2007, for example, r = 0.98).
6. Brief descriptions of it and the other variables used in the study appear in the appendix.
7. The earliest year for which the democracy index is defined in its present form is 1999. Prior to 1999, it
did not include the category of corruption.
8. See, for example, Lipset (1960) and Przeworski, Alvarez, Cheibub and Limongi (2000).
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EVGENI PEEV/DENNIS C. MUELLER
countries. The high democracy scores for the CEE countries are in line with
Kitschelt’s predictions based on the communist legacy in these countries.
The democracy scores for the FSU countries all fall between four and the
maximum possible seven. Scores above six imply virtual dictatorships. By 1999,
all FSU countries had settled down into some form of electoral authoritarianism
or outright authoritarianism.9 This pattern is also consistent with Kitschelt’s
predictions based on the communist legacy in these countries. Elections are
typically held in FSU countries, but the results are foregone conclusions long
before votes are counted, and presidents routinely are reelected with 80 percent
or more of the votes cast. The atrophying of democracy in Russia is still visible
during the first years of the 21st century, as its democracy index rises by nearly
one and a half points between 1999 and 2007, indicating a substantial weakening
of the strength of its democratic institutions. Indeed, every FSU country had a
higher Freedom House score (weaker democratic institutions) in 2007 than in
1999. In contrast, only three of the remaining 13 countries in Table A2 had
higher democracy index scores in 2007 than in 1999.
All of the transition countries either wrote new constitutions at some time after
the collapse of communism, or radically modified earlier constitutions, perhaps
dating back to before communism. When choosing political institutions, transition countries could select between a parliamentary system with weak or nonexistent president, a strong presidential system, or something in between. The
last two columns of Table A2 report transition countries’ scores for system of
government from the World Bank’s Database on Political Institutions (DPI). A
score of zero implies a strong presidential system, two a pure parliamentary
system, with scores between 0 and 2 representing mixed systems. In the far right
column are the classifications of Metelska-Szaniawska (2009) based on a careful
reading of each country’s constitution. The two classifications are in substantial
agreement. The simple correlation between the DPI system score and the democracy score for 2007 is -0.68, and between the DPI and the mean democracy score
-0.64. Thus, strong presidential systems are closely associated with authoritarianism, and parliamentary systems with strong democratic institutions. This need
not be the case, of course. The United States is a strong democracy with a strong
president. In the transition countries, however, it would appear that those countries that remained authoritarian simply institutionalized this choice by creating
a presidential system. In addition, countries which started off in the direction of
being strong democracies, like Russia and the Kyrgyz Republic, but instituted
strong presidential systems, appear to have succumbed to the temptation
afforded by a presidential system to become authoritarian.
9.
For discussions of these concepts and regimes, see Levitsky and Way (2002), Diamond (2002) and
Schedler (2002).
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
3. Economic freedom
Economic freedoms were, of course, severely restricted under communism and
at the start of the transition process. As with democratic institutions, economic
freedoms have strengthened at varying speeds or in some cases hardly at all, in
the transition countries. In this study, we measure the strength of economic
freedoms using indexes of Economic Freedom produced by the Heritage Foundation. Many studies use instead the index of economic freedom of the Fraser
Institute. For our purposes, the Heritage Foundation indexes have some advantages over the Fraser index. The Heritage Foundation updates its data on an
annual basis while the Fraser index presents data only for five year periods.
Because economic institutions were changing quite rapidly in transition countries over this time period, annual data are a great advantage. The Heritage
Foundation has also maintained a consistent rating methodology over time. It
covers all transition counties starting with 1994.10
Some studies have used EBRD indicators to measure institutional change in
transition. EBRD has published annual ratings of transition countries measuring
their progress in market reforms. However, the EBRD indicators are designed as
benchmark indicators focusing on the distance to the post-communist transition
goal (“functioning market economy”). Thus, in the late transition years they
produce rather homogenous ratings for the most advanced transition economies
(e.g., the Baltic States and CEE countries). They are more suitable for distinguishing between more advanced and less advanced transition countries rather than to
study emerging market economies completing their transition from communism.
As noted above, studies examining the relationship between economic
freedom and growth typically use overall measures of economic freedom that
aggregate various individual freedom indexes.11 However, Heckelman and
Stroup (2000, 2005) point out that the weights on the elements aggregated into
a single index often do not appropriately reflect the magnitude and even the
direction of each element’s marginal effect on growth. We thus keep the individual economic freedoms measured by the Heritage Foundation separate. A
couple of these, like government size, can only loosely be called economic
freedoms, but others like the strength of property rights and freedom from
corruption capture important dimensions of institutional quality. We focus on the
seven components of the index that seem to measure institutional quality with
respect to economic freedoms best.
We believe that the size of the state is also potentially an important determinant of economic growth, but treat it as a separate variable rather than as a
10.
11.
Although both the Heritage Foundation and Fraser indexes differ in their coverage some authors
conclude that they produce similar ratings for the countries covered (De Haan and Sturm, 2000).
For a survey see De Haan, Lundström and Sturm, 2006).
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EVGENI PEEV/DENNIS C. MUELLER
component of economic freedom. Table A3 reports the first values of the measures of economic freedom recorded by the Heritage Foundation for the year 1994
and the figures for 2007. Brief definitions of each economic freedom appear in
the appendix. Since all countries in our study had communist governments until
1989 or 1991, one might expect that the measures of economic freedom would
start low and rise through 2007. For many countries this was the case, but not for
all. The indexes run from zero to one hundred, with 100 being the maximum
possible economic freedom. The Heritage Foundation gave the Czech Republic
the implausibly high score of 100 in 1994 for business freedom and only
somewhat under 64 for this index in 2007. In general, the numbers in TableA3
reveal considerable variation both over time and across countries. The CEE and
Baltic countries tend to have the highest levels of economic freedom of the
different country groups. As with democracy, economic freedom seems to have
declined in Russia over the time period for most measures of economic freedom.
4. Public sector size
As noted in the previous subsection, government size is treated as a separate factor
affecting economic growth. Table A4 presents EBRD figures for general government expenditures in 1995 and 2007. Since in some sense, the state controlled the
whole economy under communism, one might expect the size of the public sector
to be close to one at the start of the period and decline over time. The EBRD counts
as government expenditures only state outlays for traditional public goods and
transfers like roads and unemployment compensation, however, with publicly
owned enterprises not included. Thus, the state sectors in several FSU countries
like Turkmenistan, Armenia and Kyrgyzstan were quite small in 1995, and
became even smaller over time. On average, the CEE countries have the largest
public sectors in 2007, the FSU countries the smallest. Although large public
sectors may contribute to social welfare, and thus indicate that citizens in CEE
countries are better off in some meaningful sense than citizens in the FSU
countries, the negative incentive effects from high tax rates to finance large public
sectors are expected to have negative effects on economic growth.
Immediately following the collapse of communism all transition countries
suffered steep declines in GDP. Government revenue sources collapsed while
outlays for unemployment compensation and other welfare expenditures
increased. Thus, in 1995 most transition countries were running budget deficits.
In several countries the deficits exceeded 5 percent of GDP, and in Kyrgyzstan it
was more than 17. Large budget deficits raise borrowing costs and can drive out
private investment. They also portend of large future interest payments and
higher future taxes. We thus expect that fiscal balance – government deficit
(negative) or surplus (positive) – will be related to the growth rates in the
transition countries. This variable may also proxy for the quality of a country’s
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
governmental institutions. Transition countries that were able to bring their
deficits under control are likely to have had greater success in other areas of
reform that contribute positively to growth.
The last two columns of Table A4 report measures of economic growth –
ratios of GDP per capita in 2007 and 2004 to GDP per capita in 1995. The three
Baltic countries have quite high growth rates since 1995, the five SEE countries
performed rather poorly. Some FSU countries had quite high growth rates since
1995 (Armenia, Belarus, Azerbaijan and Georgia), others quite low rates
(Moldova, Tajikistan and Turkmenistan). The growth figures in Table A5 indicate considerable variation across the transition countries.
The numbers in Tables A1-A4 lend themselves to different interpretations.
Peter Murrell (2003) looking at roughly the first decade of transition observed
“solid improvement” in institutional quality across the transition countries and
reached a rather optimistic conclusion about the success of the transition process.
Given their state of economic development, transition countries looked about the
same as developing countries in other parts of the world. Shleifer and Treisman
(2005) reached a similar conclusion for Russia. Russia was just another developing country, no better, no worse.
Gur Ofer (2003) looking at the same time period as Murrell was somewhat
pessimistic, on the other hand. “The tasks and challenges of the newly established governments in TEs (transition economies), especially during the transition years were much more difficult than those in DEs (developing economies),
and. . .the preparation and tools available to TEs, especially the weaker
ones. . .were on balance poorer. Indeed TEs suffered from a devastating combination of missing economic and political and social tools, destroyed under the
old regime. . .” (Ofer, 2003, p. 70).
Both Murrell and Ofer agreed, however, that a great difference existed
between the FSU countries and the rest of the transition countries. This difference is readily apparent in Tables A2 and A3. Moreover, the data in these tables
indicate that some transition countries have succeeded in overcoming the disadvantages that they inherited from communism, and have developed rather good
democratic and economic institutions. We now examine the interrelationships
among these developments.
III. TESTING FOR RELATIONSHIPS AMONG DEMOCRACY,
ECONOMIC FREEDOM AND GROWTH
1. The determinants of democracy
The political science literature has firmly established a positive relationship
between income per capita in a country and the probability of its being a
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EVGENI PEEV/DENNIS C. MUELLER
democracy.12 Education might be yet another determinant of democracy,
although it is likely to be linked to income also. A look at the democracy scores
in Table A2 and a map of Eurasia suggests a third determinant of democratization in the transition countries – their distance from the European Union. We thus
construct a third variable, Dist, the distance of a country’s capital city to Brussels
using internet sources.13 An alternative interpretation of the data would be that it
is not the pull of the European Union that made CEE and SEE countries choose
democracy, but the influence of Russia that led FSU countries to stick with
authoritarian governments. It is the distance to Moscow and not to Brussels that
is important. Since the two distance measures are highly correlated, one will
work as well as the other, and we stick with Brussels as the attraction point. Our
model of the determinants of democracy, thus, includes Dist, initial GDP per
capita, Y90, and initial education measured as university enrollments, EdTer90,
with the Freedom House index of democracy for the years 1999 to 2007, Demt,
being the dependent variable.14 We use annual observations of the democracy
index rather than an average or the end value, because there is so much variation
over time, and a single number would conceal much of this variation.
Since our initial conditions remain fixed, while the democracy scores change
over time, it is possible that the coefficients vary with time. Separate regressions
using the annual democracy scores indicated a non-linear pattern for the coefficients on Dist, which we allowed for by interacting this variable with time, t, and
t2. Non-linear patterns were also observed for the other two variables. The results
are as follows (t-statistics below the coefficients).15
Dem t = 3.98 − 0.14 t ⋅ Y90 + 0.012 t 2 ⋅ Y90 + 0.018 t ⋅ EdTer90
14.56
7.96
5.75
4.48
− 0.0015t 2 ⋅ EdTer90 + 0.00033t ⋅ Dist
2.61
10.96
− 0.00003t 2 ⋅ Dist, N = 216, R 2 = 0.67.
6.92
Recalling that higher democracy scores mean weaker democracy, we expect
negative coefficients on the initial income and education variables and a positive
coefficient on distance. The interaction between education and time is significant
but with the wrong sign. Thus, with respect to the importance of human capital
for economic growth, transition countries do not perform like other developing
12.
See again, Lipset (1960) and Przeworski, Alvarez, Cheibub and Limongi (2000) and the references
therein.
13. A distance variable was previously used by Fidrmuc (2003), but he did not provide precise estimates
for a few countries, setting them at the same arbitrarily high value.
14. We also estimated the model with secondary school enrollments. It too picked up the wrong sign, so
we report only the results for tertiary education.
15. When 1990 education figures were unavailable, 1995 figures were substituted to ensure that all
countries are in the regression.
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
countries (see again, Glaeser, La Porta, Lopez-de-Silanes and Shleifer, 2004).
(Education’s perverse performance might be due to multicollinearity, however.
The simple correlation between distance and tertiary enrollments is 0.23.)
Initial income has the predicted negative sign and is statistically significant.
The significant positive coefficient on t2·Y90 indicates that the relationship
between democracy and initial income grew stronger during the first few years of
transition, but then tapered off. The coefficient on distance is positive and
significant, and rises with time peaking in 2005, the year after the first wave of
post-communist countries entered the European Union. It then declines for the
next two years, but remains positive. The steady increase until the first wave of
transition countries entered the EU reflects the increasing separation of the
transition countries as time elapsed.
Thus, relatively rich post-communist countries lying close to the European
Union were the ones that successfully adopted democratic institutions. Although
distance and initial income are both significant in the equation, the fact that
initially poor Slovakia did successfully democratize, and relatively rich Russia
and the Ukraine did not, suggests that proximity to the EU was a primary driving
force behind democratization in the transition countries, and perhaps that proximity to Russia hindered democratization.
As discussed above, Kitschelt (1999) attributes the institutional choices of
transition countries to structural factors and bureaucratic legacies present before
communism’s demise. To test this hypothesis, we add the variable, ComLeg, to the
above equation. Some problems in using and interpreting this variable should be
noted, however. In addition to its somewhat subjective nature as a measure of
preconditions in the transition countries, its use in a regression equation implies
that the difference between the preconditions in Moldova and Georgia (scores of
0 and 1) has the same marginal impact on their democratic development as the
difference between Hungary and the Czech Republic (scores of 2 and 3). In
addition, as is readily apparent in the ComLeg scores reported in Table 1, there is
a high correlation between our distance from Brussels variable and Kitschelt’s
ComLeg scores. Thus, each is likely to detract from the explanatory power of the
other. Once again we allow the effect of ComLeg on democracy to vary over time.
Dem t = 3.91 − 0.004 t ⋅ Y90 + 0.014 t ⋅ EdTer90 + 0.0011t 2 ⋅ EdTer90
16.48
0.60
3.99
2.28
+ 0.00010 t ⋅ Dist − 7.9E −06 t 2 ⋅ Dist − 0.49t ⋅ ComLeg
3.67
2.20
8.83
+ 0.042 t 2 ⋅ ComLeg, N = 216, R 2 = 0.79
6.30
The two coefficients on the ComLeg terms are highly significant and imply
that the relationship between a favorable communist legacy and the subsequent
adoption of democratic institutions strengthened over time, peaking as with the
distance variable in 2005.
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EVGENI PEEV/DENNIS C. MUELLER
Table 1.
Part A. Economic Freedoms, Government Expenditures and Growth
The table presents estimates of the equation:
Gct = aGEct + bEFct + cGDPct-1 + dINVct + eGPOct + et.
GE
GDP
INV
GPO
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.164
(3.56)**
2.13
(2.42)**
0.173
(2.15)*
-41.165
(0.60)
0.014
(0.42)
-0.147
(3.32)**
1.648
(1.97)*
0.162
(2.10)*
-28.78
(0.44)
-0.122
(2.83)**
0.647
(0.77)
0.148
(1.94)*
-63.01
(0.97)
-0.172
(3.75)**
2.08
(2.45)**
0.177
(2.28)*
-28.44
(0.42)
-0.170
(3.78)**
1.90
(2.22)*
0.176
(2.25)*
-32.23
(0.48)
-0.158
(3.38)**
2.206
(2.53)**
0.178
(2.26)*
-45.37
(0.65)
-0.22
(4.46)**
1.158
(1.35)
0.165
(2.12)*
-19.90
(0.30)
Trade
0.126
(2.90)**
Monetary
0.108
(4.06)**
Investment
0.029
(1.18)
Finance
0.029
(1.41)
-0.005
(0.25)
Prop. Rights
Corruption
Constant
Observations
R-squared
-13.49
(1.99)*
322
0.08
-17.55
(2.57)**
322
0.12
-7.07
(1.10)
322
0.16
-13.48
(1.99)*
322
0.09
-11.95
(1.78)*
322
0.09
-13.37
(1.97)*
322
0.08
0.118
(2.76)**
-5.519
(0.80)
322
0.11
Robust t statistics in parentheses
* significant at 5%; ** significant at 1% using a one-tail test.
Notes: Dependent variable (G) is the annual growth rate of real per capita GDP in 2005 US dollars.
GE is total government expenditures as percentage to GDP. EF denotes economic freedoms: Business,
Trade, Monetary, Investment, Finance, Property Rights, Corruption (see Appendix, for definitions).
GDP is logarithm of annual real GDP per capita lagged one year. INV is investment as percentage to
GDP. GPO is growth in population. Subscript c stands for country and t for year.
Sources: Penn-World Table Version 6.3; EBRD; Heritage Foundation.
Thus, the different legacies from the communist era had a more pronounced
effect on the adoption of democratic institutions with the passage of time, as
some moved toward becoming full-fledged democracies and EU membership,
and others remained behind.
By 2004 the implied coefficient on ComLeg is around – 0.9, which implies a
difference in the democracy index for the Czech Republic with ComLeg = 3, and
Armenia (ComLeg = 0) of about 3, which is what we observe. With ComLeg
added, initial income becomes insignificant (also true with an interaction term
with t2). A bad bureaucratic legacy from communism might have caused lower
initial incomes in several FSU countries explaining why Y90 loses explanatory
power when ComLeg enters the equation. The coefficients on distance retain
their signs and remain significant, although with smaller values. Thus, both
382
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
Table 1.
Part B. Economic Freedoms, Fiscal Balance and Growth
The table presents estimates of the equation:
Gct = aFBct + bEFct + cGDPct-1 + dINVct + eGPOct + et.
FB
GDP
INV
GPO
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.669
(5.98)**
-0.576
(0.76)
0.10
(1.27)
-13.76
(0.21)
0.029
(0.86)
0.631
(6.15)**
-0.746
(1.01)
0.097
(1.30)
-6.545
(0.10)
0.598
(5.95)**
-1.46
(2.01)*
0.084
(1.13)
-43.295
(0.68)
0.709
(6.05)**
-0.799
(1.13)
0.106
(1.39)
-7.01
(0.10)
0.683
(6.01)**
-0.892
(1.22)
0.107
(1.40)
-3.922
(0.06)
0.656
(5.67)**
-0.408
(0.54)
0.111
(1.45)
-18.61
(0.28)
0.683
(6.17)**
-1.40
(1.71)*
0.104
(1.36)
-1.52
(0.02)
Trade
0.126
(3.07)**
Monetary
0.107
(4.33)**
Investment
0.047
(1.87)*
Finance
0.037
(1.81)*
Prop. Rights
0.003
(0.16)
Corruption
Constant
Observations
R-squared
7.50
(1.23)
322
0.14
1.97
(0.32)
322
0.18
10.70
(1.82)*
322
0.22
8.906
(1.51)
322
0.15
10.09
(1.66)*
322
0.15
7.45
(1.20)
322
0.14
0.073
(2.06)**
14.37
(2.14)*
322
0.15
Robust t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: FB is general government balance as percentage to GDP. For the other variables, see Table 7A.
Notes.
history in the form of a country’s communist legacy, and the future in the form
of expectations (hopes) of entering the European Union help explain the adoption of democratic institutions in the former communist countries.
2. Democracy, economic freedom and the size of public sector
Several scholars have argued that economic liberalism fosters political liberalism. Freedom of choice and action in the market induces people to want and get
freedom of choice in the political arena.16 North, Wallis and Weingast (2006)
have put forward the parallel thesis that the economic and political systems of a
country must be in balance – free entry into a competitive political system must
be matched with free entry into a competitive economic system. Closed economies are paired with closed political systems. Throughout history most countries
16.
Friedman (1962), Bobbio (1990), and Diamond 1995).
© 2012 Blackwell Publishing Ltd.
383
EVGENI PEEV/DENNIS C. MUELLER
have been authoritarian regimes of one sort or another in which economic
freedoms were highly constrained. Free entry into the political process did not
exist, nor was it possible to enter into economic activity freely. Most countries,
which combine competitive political systems with competitive market economies, are fairly new on the world’s stage.
All of the countries examined in this study were dictatorships with closed
economies until 1989 or 1991. In the early transition years, rapid democratization took place in some, and political liberalization often preceded economic
reforms.17 Some transition countries have thus become reasonably free and
competitive democracies. Others, however, have remained or quickly reverted
back to authoritarianism. Some authors have found a high correlation between
political freedom and economic liberalization.18 The North et al. thesis would
lead us to expect greater economic freedoms in the former communist countries,
which have become reasonably strong democracies, and this is what we observe.
The five CEE and three Baltic countries have the highest democracy scores
(Table A2) and relatively high economic freedom scores (Table A3) compared to
the SEE and FSU countries. This association is also apparent when one examines
the simple correlations between the various measures of economic freedom and
the democracy index (see Table A5). They all fall in the range -0.42 to -0.76.
As noted above, the Heritage Foundation also treats the size of the public
sector and fiscal balances as measures of economic freedom. We do not adopt
this interpretation, but believe that these variables will be associated with economic growth. Table A5 also includes the correlations between democracy, the
economic freedoms and the two measures of public sector size. The correlations
between democracy, the economic freedoms and the measures of public sector
size are for the period 1998 - 2007. Democracy and government expenditures are
highly correlated (r = -0.55). Citizens in the more democratic transition countries
appear to want larger public sectors and are able to get their governments to
supply them. In doing so, governments in the more democratic countries also
tend to run bigger government deficits (smaller surpluses, r = 0.21).
The correlations between the democracy scores and government spending are
open to an alternative interpretation, however. We have seen in Table A2 that
strong democratic institutions are correlated with the existence of parliamentary
forms of government, while weak democracy is associated with strong presidential systems in the transition countries. Persson and Tabellini (2000, 2003) have
developed a model, which predicts large public sectors in multiparty parliamentary systems, because of the need to form broad coalitions of interests in these
systems. They predict and find smaller public sectors in countries with presidential systems than in multiparty parliamentary systems. The correlation between
17.
18.
384
See, Fidrmuc (2003).
See, de Melo, Denizer and Gelb (1996), Dethier et al. (1999), and Fish (2003).
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
democracy and state spending in the transition countries might be due to the fact
that the countries with strong democratic institutions overwhelmingly have multiparty parliamentary systems. The Persson and Tabellini model, however,
assumes that political competition also exists in presidential systems. This is not
the case for the transition countries. Thus, whether the correlations in Table A5
corroborate Persson and Tabellini cannot really be determined. In the transition
countries authoritarianism and presidential systems are too closely entwined.
Government expenditures are also highly correlated with a few of the indexes
of economic freedoms. In particular, large public sectors are strongly correlated
with low levels of corruption (r = 0.58), strong property rights enforcement
(r = 0.47), and financial markets liberalization (r = 0.35).
3. The determinants of growth in transition countries
Several studies have established a link between economic freedoms of various
sorts and economic growth.19 Thus, the first causal chain that we identify posits
that strong democratic institutions determine strong economic freedoms, which
in turn lead to more rapid economic growth. Alternatively, one might think of
democracy and economic freedoms being jointly determined by the initial conditions identified above including legacy from communism. We depict it as a
single causal change, however.
Democracy → Economic Freedom → Economic Growth
Most studies that look at the relationship between economic freedoms and
growth, measure growth over a span of years and use one or more of the
following three measures of economic freedoms: initial values, an average over
the time period, or the change in economic freedoms over the time period. Some
studies include both the initial values and the change in the measure. Thus, if EF0
is the value of a measure of economic freedom at the beginning of the time
period, EFn is its value at the end of the period, and G is the growth rate, they
estimate an equation looking like G = aEF0 + b(EFn – EF0) + m. But this is
equivalent to estimating a model that includes just the initial and ending values
of EF, G = (a - b)EF0 + b EFn + m.20 Such a model will suffer from endogeneity
problems, if a country’s economic growth has a feedback effect on its economic
institutions and economic freedoms.
Because we have so few time series observations, measuring growth over a
span of years would effectively limit us to a single cross-section regression with
at most 24 observations (one per country). Moreover, using an average of an EF
19.
20.
See, for example, Knack (1996), Knack and Kiefer (1995), De Haan and Sturm (2000), Heckelman
(2000), Heckelman and Stroup (2000), and for a survey De Haan, Lundstöm and Sturm (2006).
See discussion in De Haan, Lundstöm and Sturm (2006).
© 2012 Blackwell Publishing Ltd.
385
EVGENI PEEV/DENNIS C. MUELLER
measure over the sample years would disguise the considerable variation in
economic freedoms that took place in many of the transition countries during
the years of our study. On average, the standard deviation of the total index of
economic freedom in transition countries is 9.45 (mean score 56.87), much
larger than the standard deviation of the same index in EU-15 countries, 5.62
with mean of 66.87. We have thus chosen to use annual rates of growth in
income per capita on the left-hand-side of the equation and annual measures of
economic freedoms and the other variables. This choice of annual data finds
further support in recent work by Mollick and Cabral (2011) who show that
averaging annual data over five-year time spans mutes the effects of variables
with considerable variation within the time span.21 Thus, our specification
allows us to capture the effects of changes in economic freedoms over time.
According to De Haan and Sturm (2000), the change in an EF variable on the
right-hand-side of a growth equation is the most robust specification of such a
model.22 Our use of panel data effectively allows us to capture the effects of
both levels of EF through the cross-section variation in the data, and changes in
EF through the time-series variation. Our specification does not, however,
address a question that concerned several earlier studies of growth in the transition countries – namely whether rapid institutional reforms at the start of the
transition process produced higher levels of growth than gradual reforms.23 We
leave out the initial years, when rapid liberalization was occurring in some
transition countries, and thus hope to be estimating the long-run relationship
between institutional quality and growth.
A large literature has explored the relationship between the size of the public
sector and economic growth. It is well-established that the size of the state sector
in developed and developing countries, at least after some point, is negatively
related to economic growth.24 Much of this literature uses US data on local and
state expenditures, but a fair number of studies have also used cross-national
data. As yet, however, relatively little work in this area has focused on transition
countries. For example, in a comprehensive survey of studies of economic
growth in transition, Campos and Coricelli (2002) report only a few, which look
at the effects of the size of the state on growth.25
In the broader literature, some studies have reported a negative, insignificant
link,26 while others find a non-linear relationship, still others find no relationship
21. Eberhardt and Teal (2009) also present evidence of the superiority of annual data in growth equations.
22. See again De Haan, Lundstöm and Sturm (2006).
23. See de Melo, Denzier and Gelb (1996), Heybey and Murrell (1999), and Godoy and Stiglitz (2006).
Heybey and Murrell present a nice review of the literature.
24. See, Barro (1991) and the survey of the literature in Mueller (2003, pp. 548–54).
25. See e.g. Chu Ke-young and Gerd Schwartz (1994), Kornai (1995), Coricelli (1997), and Dabrowski
(1997).
26. See, Beck and Laeven (2005).
386
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
between the size of the public sector and economic growth, and a few have even
found a positive relationship – large public sectors foster growth. However, the
most typical finding has been that a large public sector is associated with slower
economic growth.27 This finding adds another dimension to the above link
between democracy and economic growth. A dictatorship might, of course, have
either a very large or a small public sector. Dictators often live very lavishly at
the public’s expense. But a few palaces and Mercedes are unlikely to make as big
of a dent in the public budget as a generous transfer system. Citizens may also
demand more spending on roads, schools and other public goods than a dictator
would choose to spend. We thus expect a negative relationship between authoritarianism and the size of the public sector, or stated differently, a positive
relationship between the strength of democratic institutions and the size of the
public sector. Combining this hypothesis with the prediction that large public
sectors lead to slow economic growth due to the negative incentive effects of
high taxes leads to the following causal chain.
Democracy → Large Public Sector → Slow Economic Growth
Many types of government expenditures are popular with voters – education,
police protection, highways. Taxes are never popular. Thus, elected politicians
are more likely to introduce higher spending than higher taxes. Dictatorships
might also be less prone to run deficits because bond markets are unwilling to
buy their debt out of fear that the dictatorship will fail to honor its obligations.
These considerations lead to the expectation of bigger budget deficits (smaller
surpluses) in countries with strong democratic institutions.
Budget deficits lead to higher taxes to service the debt, which in turn have the
usual disincentive effects of all taxes. As noted earlier, all transition countries
had deficits at the beginning of the period under investigation, so that the size of
deficits (surpluses) later in the period measures the success of countries in
removing deficits and thus might be regarded as a measure of the quality of
governmental reforms. We, thus, expect budget deficits to have a negative association with economic growth.
Democracy → Large Budget Deficits → Slow Economic Growth
We test these hypotheses by regressing country growth rates on various measures of public sector size and economic freedoms. In doing so, we treat democracy as a latent variable explaining both public sector size and economic
freedoms. In the regressions to explain economic growth, we also include standard control variables from the growth literature –total capital investment as a
27.
See, Pushak et al (2007).
© 2012 Blackwell Publishing Ltd.
387
EVGENI PEEV/DENNIS C. MUELLER
share of GDP, and the growth in population.28 We also attempt to control for the
frequently observed “catch-up” phenomenon. Since we use annual growth rates
as the dependent variable, however, we do not use the income per capita for each
country at the start of the time period to test the catch-up hypothesis. Instead,
we us the lagged, annual deviations in each country’s GDP per capita from
the sample mean to test the catch-up hypothesis. This formulation allows us
to take into account that some countries are catching up at different rates
than others.
Conspicuous in their absence from out growth equations are measures of
human capital. We have seen for the transition countries, however, that school
enrollments were relatively high in all of the countries, and that the shift to
democracy was not associated with initial levels of school enrollment, or even
perversely related. School enrolments in 1990 also do not explain subsequent
growth rates in transition countries. Indeed, their coefficients are typically
negative and often statistically significant, when added to the growth equations. This is not surprising when one examines the school enrollment rates
and growth figures in Tables A1 and A4. Estonia had a high growth rate, but
not particularly high school enrollments. Russia and the Ukraine had high
university enrollments, but only middling growth performance. Therefore,
we do not report results including initial school enrollments in the growth
equations.
IV. RESULTS FOR GROWTH EQUATIONS
Table 1 presents regression results testing the second parts of the three causal
chains described above. The dependent variable in all cases is the annual growth
in GDP per capita of country c in year t, Gct. The data span the period 1994 to
2007. Part A of Table 1 presents results including the size of the public sector,
while Part B substitutes government fiscal balance for government size.
Most coefficients on the economic freedom measures have the expected positive signs, with three of the seven (trade freedom, monetary freedom and
freedom from corruption) being significant at the one percent level. When all
seven economic freedom indexes are included in the same equation, there is
obviously considerable multicollinearity.29
The government size variable is negative in all eight equations in Part A, and
is significant at the one percent level in all equations. Larger public sectors in the
transition countries are associated with slower economic growth. The coefficients on the two of the control variables (investment and population growth)
have the correct signs in the seven equations with a majority of them being
28. See discussion in Temple (2000).
29. See, Heckelman and Stroup (2005) for discussion on the aggregation procedures producing a single
index value.
388
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
statistically significant.30 The coefficients on deviations from the mean lagged
GDP per capita are all negative, as predicted under the catch-up hypothesis, with
all but two being significant at the ten percent level or better.
Part B of Table 1 substitutes the government surplus for the size of government. All seven economic freedom indexes have the predicted positive signs,
with five of the seven significant at five per cent level, one-tailed test. The budget
surplus always has the predicted positive coefficient and is highly significant in
all equations. In addition to capturing the drag on economic growth from running
deficits, the government surplus is presumed to measure the competence of
governments. Well-managed public sectors exhibit budget surpluses (small deficits) and high economic growth. Inclusion of the government balance detracts
from the explanatory power of investment. Perhaps this is because large budget
deficits reduce investment by raising country interest rates. Both the lagged
deviations in GDP per capita and population growth are generally statistically
insignificant with population growth having the predicted negative coefficients,
and lagged deviations in GDP per capita having the wrong, positive coefficients.
Although the control variables do not perform very well when fiscal balance is
included in the model, its performance and that of the economic freedom variables do generally support the main hypotheses put forward in this article.
Although we interpret government surpluses as proxies for the quality of
political governance, it is possible that causality is running in the opposite
direction – rapid growth raises tax revenue and reduces deficits (increases surpluses). We attempted to test for this possibility by estimating a two equation,
three-stage-least-squares model with growth and budget surpluses as endogenous variables. Growth was never significant in the budget surplus equation, but
most of the other variables we tried were also insignificant. We simply could not
come up with a decent model to explain government surpluses. The proper
interpretation of the coefficient on budget surpluses in Table 1B and subsequent
tables must thus be left to the reader.
V. ADDITIONAL TESTS
1. Results with country fixed effects
Growth equations are vulnerable to several econometric problems.31 In crossnational regressions, for example, an omitted variable might be relevant for a
subset of countries, but perhaps not all. For example, several transition countries
have large ethnic minorities. Their presence might lead to political discord,
30.
Some studies focusing on the transition years before 2000, do not find significant negative effects of
government size and significant positive effects of investment on growth (see e.g. Campos, 2001;
Fidrmuc, 2003).
31. See, Temple (2000).
© 2012 Blackwell Publishing Ltd.
389
EVGENI PEEV/DENNIS C. MUELLER
which adversely affects economic growth. To control for such possibilities, we
re-estimate our models after including country fixed-effects. Country fixed-effect
dummies also control for preconditions peculiar to each country, which might
affect the speed and extent of adoption of reforms that influence growth.
Although these results can simply be viewed as a robustness check, they provide
some additional insight into what has been going on in the transition countries.
Table 2 presents the results. The coefficients on the country dummies represent
differences from the sample mean.
Regressing annual growth rates on the full set of country dummy variables for
the transition countries, yields an adjusted R2 of essentially zero. When they are
added to the various equations whose estimates are reported in Part A of Table 2,
however, they produce significant increases in explanatory power. With government size in the regressions, the coefficients on trade freedom, monetary freedom
and freedom from corruption are statistically significant and of the correct sign.
When government size is replaced by fiscal balance, again only trade and
monetary freedom, and freedom from corruption have the predicted positive
coefficients and are statistically significant (Table 2B).
The coefficients on both government size and the deficit increase in size and
significance once country fixed-effects are controlled for. A ten percentage point
increase in the size of the public sector is now expected to reduce a country’s
annual growth by two percentage points. A reduction of the budget deficit by one
percent of GDP increases a country’s growth rate by slightly more than 0.8
percentage point.
The control variables perform less consistently with country fixed-effects. The
lagged GDP per capita and population growth are never negative and significant
as predicted, and even have a positive and significant coefficient in some equations. Investment has a positive and significant coefficient in a few equations
when government size is included (Table 2A).
The coefficients on the country dummies contain some interesting insights as
to the reasons why transition countries exhibit different growth rates. We saw in
Table A4 that Estonia had one of the highest average growth rates among the
transition countries. Yet its dummy variable is generally insignificant. Estonia’s
rapid growth appears to be well explained by the economic freedom, government
size, and fiscal balance variables, along with the control variables. In contrast,
Turkmenistan had quite low growth over the sample period, and its coefficient is
negative and usually highly significant. Although Turkmenistan failed to liberalize its economy as much as the central European countries did, this alone does
not explain its poor growth performance.
We conclude that there are some important country differences in growth
performance that cannot be accounted for by the other variables in the model.
Among the economic freedom variables, only trade freedom, monetary freedom
and freedom from corruption appear to be robust to all specifications and thus are
390
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
Table 2.
Part A. Economic Freedoms, Government Expenditures and Growth (Fixed Effects)
GE
GDP
INV
GPO
Albania
Belarus
Armenia
Azerbaijan
Georgia
Croatia
Slovak Rep.
Poland
Lithuania
Latvia
Estonia
Kazakhstan
Kyrgyz Rep.
Macedonia
Romania
Turkmenistan
Tajikistan
Moldova
Bulgaria
Czech Rep.
Russ. Fed.
Hungary
Slovenia
Ukraine
Business
Trade
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.236
(2.92)**
3.27
(1.63)
0.143
(1.69)*
369.44
(3.10)**
0.397
(0.15)
3.75
(1.51)
5.54
(2.51)**
-1.68
(0.59)
4.84
(1.93)*
1.84
(0.79)
0.262
(0.11)
1.42
(0.66)
-0.072
(0.04)
4.82
(2.18)*
3.98
(1.55)
-2.57
(1.15)
-6.98
(2.34)**
-3.49
(1.33)
-0.87
(0.49)
-11.76
(3.93)**
-8.34
(1.96)*
0.66
(0.25)
3.84
(1.82)*
-2.14
(0.82)
1.62
(0.62)
-0.68
(0.36)
-1.01
(0.36)
3.34
(1.58)
-0.019
(0.35)
-0.189
(2.33)**
0.519
(0.24)
0.153
(1.85)*
381.20
(3.26)**
-0.509
(0.19)
5.62
(2.31)*
3.92
(1.75)*
-2.02
(0.74)
4.44
(1.79)*
2.28
(1.02)
-0.0005
(0.01)
1.66
(0.79)
-0.73
(0.40)
4.11
(1.96)*
3.00
(1.34)
-0.489
(0.21)
-8.64
(2.91)**
-3.26
(1.27)
-1.05
(0.60)
-8.85
(3.30)**
-11.11
(2.61)**
-2.48
(0.89)
4.61
(2.21)*
-1.49
(0.61)
2.14
(0.84)
2.04
(0.97)
1.12
(0.40)
3.22
(1.59)
-0.124
(1.57)
-4.54
(1.92)*
0.136
(1.70)*
338.65
(3.00)**
-6.28
(2.25)*
12.28
(4.51)**
1.68
(0.76)
-4.67
(1.74)*
2.13
(0.87)
1.51
(0.70)
1.13
(0.51)
2.18
(1.07)
1.08
(0.61)
3.78
(1.86)*
5.30
(2.44)**
0.84
(0.38)
-11.64
(3.96)**
-7.99
(3.06)**
1.39
(0.77)
-5.83
(2.03)*
-12.79
(3.13)**
-5.40
(1.99)*
4.61
(2.29)*
0.35
(0.15)
3.04
(1.23)
3.31
(1.68)
3.57
(1.31)
2.67
(1.36)
-0.241
(2.99)**
3.25
(1.62)
0.142
(1.69)*
370.39
(3.11)**
0.69
(0.26)
3.55
(1.40)
5.56
(2.52)**
-2.13
(0.69)
4.76
(1.89)*
2.01
(0.89)
0.44
(0.19)
1.59
(0.79)
0.031
(0.02)
4.99
(2.21)*
4.39
(1.55)
-3.04
(1.22)
-7.02
(2.36)**
-3.45
(1.32)
-0.73
(0.41)
-12.16
(3.80)**
-8.73
(1.98)*
0.41
(0.16)
4.13
(1.90)*
-2.01
(0.77)
1.93
(0.70)
-0.718
(0.37)
-1.17
(0.43)
3.31
(1.58)
-0.247
(3.02)**
3.62
(1.75)*
0.142
(1.69)*
377.10
(3.14)**
0.45
(0.17)
3.47
(1.37)
5.99
(2.56)**
-1.96
(0.68)
4.73
(1.88)*
2.11
(0.93)
0.37
(0.16)
1.43
(0.67)
-0.15
(0.08)
5.02
(2.25)*
4.13
(1.69)*
-2.96
(1.26)
-6.79
(2.31)*
-3.03
(1.13)
-0.89
(0.50)
-12.77
(3.56)**
-8.55
(2.01)*
0.91
(0.34)
4.13
(1.92)*
-1.81
(0.68)
1.78
(0.68)
-0.86
(0.44)
-1.38
(0.51)
3.38
(1.64)
-0.223
(2.78)**
2.27
(1.10)
0.145
(1.74)*
393.85
(3.31)**
-1.54
(0.54)
3.10
(1.28)
5.94
(2.69)**
-3.69
(1.23)
3.43
(1.31)
0.79
(0.34)
1.37
(0.57)
3.73
(1.50)
0.85
(0.40)
5.85
(2.64)**
7.65
(2.41)**
-3.48
(1.53)
-9.40
(2.89)**
-5.13
(1.86)*
-2.35
(1.20)
-13.86
(4.46)**
-11.22
(2.49)**
0.48
(0.19)
4.06
(1.93)*
1.44
(0.44)
5.08
(1.57)
-0.70
(0.37)
0.69
(0.24)
2.20
(1.02)
-0.282
(3.53)**
2.13
(1.07)
0.111
(1.34)
372.92
(3.21)**
2.18
(0.83)
5.91
(2.44)**
4.51
(2.06)*
-0.156
(0.06)
6.44
(2.57)**
1.61
(0.72)
-0.67
(0.30)
-0.57
(0.26)
-1.45
(0.78)
4.13
(1.98)*
-0.83
(0.33)
-0.25
(0.11)
-6.91
(2.39)**
-3.01
(1.18)
-0.62
(0.36)
-8.11
(2.77)**
-6.75
(1.64)
0.84
(0.33)
3.33
(1.61)
-3.65
(1.45)
-0.61
(0.24)
1.11
(0.57)
-3.63
(1.32)
4.81
(2.34)**
Monetary
0.137
(2.98)**
Investment
0.168
(5.60)**
Finance
-0.021
(0.49)
Prop.Rights
-0.022
(0.61)
Corruption
Constant
Obs
R-squared
-17.91
(1.00)
322
0.19
-6.27
(0.35)
322
0.22
35.73
(1.84)*
322
0.20
-17.62
(0.99)
322
0.19
-20.57
(1.16)
322
0.19
-0.118
(1.83)*
-5.65
(0.30)
322
0.20
0.192
(3.53)**
-12.78
(0.74)
322
0.23
Absolute value of t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: See Table 7A. Notes.
© 2012 Blackwell Publishing Ltd.
391
EVGENI PEEV/DENNIS C. MUELLER
Table 2.
Part B. Economic Freedoms, Fiscal Balance and Growth (Fixed Effects)
FB
GDP
INV
GPO
Albania
Belarus
Armenia
Azerbaijan
Georgia
Croatia
Slovak Rep.
Poland
Lithuania
Latvia
Estonia
Kazakhstan
Kyrgyz Rep.
Macedonia
Romania
Turkmenistan
Tajikistan
Moldova
Bulgaria
Czech Rep.
Russ. Fed.
Hungary
Slovenia
Ukraine
Business
Trade
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.879
(6.77)**
0.32
(0.17)
0.044
(0.54)
220.71
(1.92)*
4.47
(1.81)*
1.06
(0.49)
7.79
(4.18)**
0.28
(0.11)
6.40
(3.15)**
0.86
(0.45)
0.22
(0.11)
0.82
(0.43)
0.032
(0.02)
2.84
(1.35)
0.76
(0.31)
-1.05
(0.57)
-2.42
(0.85)
-5.26
(2.13)*
-0.87
(0.52)
-7.39
(2.82)**
-5.35
(1.37)
-2.46
(0.99)
-0.96
(0.47)
-1.06
(0.44)
2.13
(0.95)
-3.25
(1.78)*
-1.79
(0.71)
0.33
(0.17)
-0.002
(0.03)
0.828
(6.43)**
-1.98
(0.95)
0.066
(0.84)
240.73
(2.13)*
3.24
(1.31)
3.02
(1.38)
5.89
(3.01)**
-0.69
(0.29)
5.49
(2.70)**
1.59
(0.85)
0.48
(0.25)
1.43
(0.77)
-0.436
(0.25)
2.49
(1.25)
0.40
(0.19)
0.22
(0.12)
-4.40
(1.55)
-4.97
(2.05)*
-1.13
(0.69)
-5.79
(2.37)**
-8.53
(2.17)*
-4.99
(1.90)*
0.04
(0.02)
-0.08
(0.04)
3.16
(1.45)
-0.663
(0.33)
0.62
(0.24)
0.40
(0.21)
0.684
(5.13)**
-5.10
(2.25)*
0.067
(0.88)
229.79
(2.07)*
-1.79
(0.64)
8.48
(3.20)**
3.91
(1.94)*
-3.03
(1.24)
3.41
(1.63)
1.23
(0.68)
1.43
(0.75)
1.94
(1.06)
0.95
(0.55)
2.58
(1.32)
2.68
(1.24)
0.72
(0.39)
-7.28
(2.48)**
-8.29
(3.33)**
0.80
(0.47)
-4.50
(1.85)*
-10.04
(2.60)**
-6.40
(2.47)**
0.77
(0.38)
1.06
(0.47)
3.75
(1.75)*
0.469
(0.24)
2.40
(0.94)
0.55
(0.30)
0.889
(6.83)**
0.325
(0.17)
0.039
(0.50)
211.56
(1.84)*
4.17
(1.65)*
1.59
(0.70)
7.70
(4.12)**
1.02
(0.38)
6.38
(3.14)**
0.95
(0.51)
-0.029
(0.01)
0.589
(0.31)
-0.36
(0.19)
2.36
(1.09)
-0.26
(0.10)
-0.48
(0.24)
-2.15
(0.76)
-5.19
(2.11)*
-0.97
(0.58)
-6.57
(2.38)**
-4.63
(1.16)
-2.19
(0.87)
-1.30
(0.61)
-1.48
(0.62)
1.69
(0.74)
-3.17
(1.73)*
-1.83
(0.76)
0.31
(0.16)
0.88
(6.81)**
0.408
(0.20)
0.044
(0.55)
223.25
(1.93)*
4.50
(1.82)*
0.949
(0.42)
7.93
(3.86)**
0.217
(0.09)
6.42
(3.16)**
0.87
(0.46)
0.227
(0.12)
0.812
(0.43)
0.048
(0.03)
2.91
(1.38)
0.857
(0.37)
-1.12
(0.59)
-2.39
(0.86)
-5.18
(2.06)*
-0.878
(0.52)
-7.64
(2.52)**
-5.40
(1.40)
-2.42
(0.96)
-0.912
(0.43)
-0.968
(0.40)
2.16
(0.98)
-3.31
(1.77)*
-1.87
(0.76)
0.314
(0.16)
0.855
(6.52)**
-0.155
(0.08)
0.05
(0.63)
240.26
(2.08)*
3.27
(1.21)
0.711
(0.33)
7.94
(4.26)**
-0.998
(0.37)
5.57
(2.56)**
0.255
(0.13)
0.898
(0.44)
2.16
(0.96)
0.634
(0.34)
3.56
(1.67)*
3.06
(0.99)
-1.65
(0.86)
-3.97
(1.26)
-6.16
(2.37)**
-1.71
(0.92)
-8.84
(3.18)**
-7.15
(1.71)*
-2.48
(1.00)
-0.722
(0.35)
1.02
(0.34)
4.12
(1.43)
-3.20
(1.75)*
-0.708
(0.27)
-0.272
(0.13)
0.856
(6.68)**
-0.309
(0.16)
0.019
(0.24)
233.33
(2.06)*
5.91
(2.37)**
2.13
(1.01)
7.49
(4.06)**
1.73
(0.71)
8.18
(3.87)**
0.076
(0.04)
-0.940
(0.47)
-0.958
(0.49)
0.773
(0.44)
2.53
(1.26)
-2.33
(0.96)
1.03
(0.52)
-2.37
(0.86)
-5.02
(2.06)*
-0.63
(0.38)
-4.52
(1.73)*
-3.89
(1.02)
-2.27
(0.92)
-1.31
(0.64)
-2.50
(1.06)
-0.023
(0.01)
-2.03
(1.09)
-3.95
(1.55)
1.22
(0.63)
Monetary
0.119
(2.78)**
Investment
0.129
(4.35)**
Finance
0.024
(0.59)
Prop.Rights
-0.005
(0.15)
Corruption
Constant
Obs
R-squared
3.665
(0.21)
322
0.28
14.95
(0.87)
322
0.30
42.42
(2.27)*
322
0.33
3.12
(0.18)
322
0.28
3.12
(0.18)
322
0.28
-0.065
(1.06)
10.44
(0.58)
322
0.29
0.138
(2.68)**
5.33
(0.32)
322
0.30
Absolute value of t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: See Table 7B. Notes.
392
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
possible candidates for explaining growth. With country effects accounted for,
government size and fiscal balance continue to have highly significant relationships to economic growth. The fact that the strength of democratic institutions is
strongly associated with larger government sectors and bigger government deficits indicates that the transition countries, which have developed relatively strong
democratic institutions, have ceteris paribus paid a price for their large public
sectors and budget deficits in terms of slower growth.
2. Results after dropping investment
One obvious difficulty in the growth equations is that investment might be
endogenous with respect, say, to some of the economic freedom measures. One
way to adjust for this would be to choose instruments to estimate investment.
Obvious choices would be initial income and education levels, but these also affect
the other variables in the model. We have chosen, therefore, to check for the
possibility of investment’s being endogenous, by dropping it from the equations
and seeing what this does to the other coefficients. This step can also be viewed as
a check for the sensitivity of the estimates to the preferred specification.
Table 3 presents the same regression results as Table 1, except for the omission of investment. All 14 coefficients on the economic freedom variables are
now positive, with 9 being significant at the five percent level, one-tailed test.
These results strongly suggest that economic freedoms lead to higher growth
rates in large part by stimulating investment. Only business freedom and property rights freedom have in both the equations insignificant coefficients.
The Heritage Foundation’s economic freedom indexes are a “mixed bag” in
that some clearly measure the quality of an underlying institution or set of
institutions (property rights and financial freedom, freedom from corruption),
while others measure macroeconomic policy outcomes (trade and monetary
freedoms) or industrial policy with respect to FDI (investment freedom).32 The
significant coefficients that we observe on trade freedom, monetary freedom and
freedom from corruption even with investment in the equation indicate that these
measures of institutional quality have an independent effect on growth beyond
any effect that they have on investment.
3. Combining the effects of economic freedoms
Having established that several measures of economic freedom appear to have
positive impacts on economic growth in the transition countries, we shall now
attempt to isolate any joint impacts that they might have.
32.
See definitions in the Appendix, and discussion in Heckelman and Stroup (2005).
© 2012 Blackwell Publishing Ltd.
393
EVGENI PEEV/DENNIS C. MUELLER
Table 3.
Part A. Economic Freedoms, Size of Government and Growth
GE
GDP
GPO
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
-0.167
(3.41)**
2.29
(2.55)**
-57.87
(0.79)
0.041
(1.19)
-0.148
(3.20)**
1.883
(2.17)*
-35.82
(0.53)
-0.125
(2.74)**
0.787
(0.89)
-70.63
(1.07)
-0.173
(3.56)**
2.38
(2.76)**
-45.73
(0.63)
-0.175
(3.76)**
2.12
(2.35)**
-44.12
(0.62)
-0.163
(3.24)**
2.47
(2.81)**
-61.67
(0.83)
-0.234
(4.64)**
1.17
(1.26)
-29.77
(0.43)
Trade
0.159
(3.57)**
Monetary
0.126
(4.74)**
Investment
0.034
(1.38)
Finance
0.043
(1.99)*
Prop. Rights
0.007
(0.36)
Corruption
Constant
Observations
R-squared
-12.50
(1.78)*
328
0.05
-18.05
(2.68)**
328
0.11
-5.893
(0.88)
328
0.15
-12.29
(1.75)*
328
0.06
-10.32
(1.46)
328
0.06
-11.93
(1.69)*
328
0.05
0.149
(3.42)**
-2.33
(0.31)
328
0.10
Robust t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: See Table 7A. Notes.
One can envisage two, polar possibilities. (1) The effects of the individual
measures of economic freedom are additive. Adding strong trade freedom to
strong enforcement of property rights produces additional growth. (2) The
effects of the individual economic freedoms are multiplicative. In the absence of
strong enforcement of property rights the other economic freedoms have no
impact on growth. We attempted to determine which of these possible relationships best describes the data by experimenting with various multiplicative and
additive combinations of the variables. The additive formulations always exhibited higher explanatory power than the multiplicative formulations. Due to high
correlations among the seven economic freedoms, little improvement in fit was
observed after two or three economic freedoms were included in the model. With
government expenditures as the measure of government size, the best-fit equation was (t-statistics under coefficients).
G ct = − 11.31 − 0.19GE ct + 1.04 GDPct −1 + 0.15Inv t − 15.20 PopGr + 0.10 Trade
1.59
4.08**
1.21
2.03*
0.23
2.41**
+ 0.08Corruption, N = 322, Adj. R 2 = 0.13
2.66**
With fiscal balance as the measure of government size, the best fit equations
included trade freedom and either finance freedom or freedom from corruption
394
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
Table 3.
Part B. Economic Freedoms, Fiscal Balance and Growth
FB
GDP
GPO
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.708
(6.19)**
-0.729
(0.97)
-40.09
(0.56)
0.051
(1.51)
0.660
(6.18)**
-0.793
(1.13)
-22.94
(0.35)
0.625
(6.00)**
-1.593
(2.24)*
-60.09
(0.93)
0.75
(6.38)**
-0.842
(1.24)
-18.04
(0.25)
0.729
(6.38)**
-1.04
(1.39)
-23.16
(0.34)
0.701
(5.92)**
-0.509
(0.69)
-42.97
(0.59)
0.725
(6.49)**
-1.757
(2.03)*
-18.43
(0.27)
Trade
0.154
(3.65)**
Monetary
0.122
(4.90)**
Investment
0.054
(2.18)*
Finance
0.051
(2.38)**
Prop. Rights
0.016
(0.75)
Corruption
Constant
Observations
R-squared
9.88
(1.57)
328
0.13
2.72
(0.44)
328
0.18
12.87
(2.13)*
328
0.22
11.41
(1.87)*
328
0.14
13.27
(2.07)*
328
0.14
10.44
(1.63)
328
0.12
0.100
(2.75)**
19.07
(2.68)**
328
0.15
Robust t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: See Table 7B. Notes.
(similar explanatory power). Thus, the economic freedoms that had the highest
explanatory power when included individually retained their explanatory power
when included additively.
4. The endogeneity of economic freedoms
Another possible econometric problem in the growth equations is that the economic freedoms are endogenous with respect to growth. We addressed this
possibility by estimating a two equation model using three-stage least squares.
The first equation was the growth equation from Table 1 with the mean economic
freedom score now treated as an endogenous variable. The second equation had
mean economic freedom as the dependent variable and growth, initial GDP per
capita, and either distance from Brussels or the democracy index as explanatory
variables. The results for the growth equation were similar to those reported in
Table 1. Both distance and the democracy index were highly significant in
explaining economic freedom. Initial GDP per capita did not have a significant
impact on the level of economic freedom nor, more importantly, did growth. The
© 2012 Blackwell Publishing Ltd.
395
EVGENI PEEV/DENNIS C. MUELLER
Table 4.
Part A. Government Expenditures and Growth
GE
GDP
INV
GPO
GDP Growth
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.26
(2.90)**
-2.00
(0.81)
0.13
(0.60)
457.09
(2.44)**
-0.48
(1.34)
-0.244
(-2.34)**
0.287
(3.14)**
-4.47
(1.40)
0.065
(0.41)
403.06
(3.14)**
-0.17
(0.74)
0.244
(2.21)*
-4.54
(1.63)
0.44
(0.16)
449.96
(2.17)*
-0.537
(1.32)
0.268
(3.17)**
-5.80
(2.84)**
0.66
(0.32)
296.94
(1.59)
-0.44
(1.41)
0.286
(3.93)**
-4.65
(2.25)*
0.046
(0.24)
320.06
(1.79)*
-0.457
(1.61)
0.316
(3.39)**
-0.973
(0.60)
0.101
(0.48)
519.94
(3.37)**
-0.553
(1.59)
0.333
(3.65)**
-1.16
(0.44)
0.101
(0.44)
-19.90
(0.30)
-0.560
(1.50)
-0.429
(4.58)**
Trade
-0.128
(1.91)*
Monetary
-0.148
(3.18)**
Investment
-0.176
(2.95)**
Finance
-0.17
(2.71)**
Prop. Rights
Corruption
Constant
Observations
R-squared
13.75
(0.65)
23
0.71
50.47
(1.77)*
23
0.79
31.41
(1.26)
23
0.67
41.58
(2.10)*
23
0.74
34.80
(1.68)*
23
0.75
-5.06
(0.40)
23
0.71
-0.192
(2.41)**
-4.41
(0.20)
23
0.69
Robust t statistics in parentheses
* significant at 5%; ** significant at 1% using a one-tail test.
Notes: The dependent variable is the difference between average real GDP growth in 2008–2009 and
1994–2007. GDP growth is the average growth rate over the period 1994–2007. GDP is the logarithm
of real GDP per capita in 1990. The other independent variables are averages over the period
1994–2007. For the other variables definitions see Table 7A. Notes.
positive link between economic freedom and economic growth does not disappear, once we allow for the possible feedback effect of growth on economic
freedom.33
VI. ECONOMIC GROWTH FOLLOWING THE FINANCIAL CRISIS
Our estimates of the determinants of economic growth are based on data up to the
start of the financial crisis. In this section, we examine whether the variables,
which explained economic growth prior to the crisis, also can explain the growth
performance changes caused by the crisis. Table 4 reports the results for equations using the same explanatory variables as were used in Table 1. The dependent variable, however, is now the difference between a country’s growth rate after
33.
396
These results are available on request.
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
Table 4.
Part B. Economic Freedoms, Fiscal Balance and Growth
FB
GDP
INV
GPO
GDP Growth
Business
(1)
(2)
(3)
(4)
(5)
(6)
(7)
0.013
(0.04)
-1.33
(0.43)
0.132
(0.45)
288.35
(1.74)*
-0.930
(2.28)*
-0.222
(1.64)
-0.046
(0.16)
-3.32
(1.20)
0.092
(0.35)
222.92
(1.81)*
-0.690
(1.87)*
0.138
(0.43)
-4.08
(1.28)
0.015
(0.05)
293.54
(1.74)*
-0.940
(2.29)*
-0.038
(0.11)
-4.64
(1.91)*
0.090
(0.31)
135.48
(0.74)
-0.905
(2.24)*
0.067
(0.20)
-3.81
(1.55)
0.037
(0.13)
157.46
(0.91)
-0.940
(2.65)**
0.047
(0.15)
-0.911
(0.36)
0.100
(0.33)
321.28
(2.35)**
-1.05
(2.57)**
0.201
(0.72)
-1.88
(0.66)
0.055
(0.17)
293.21
(1.74)*
-1.04
(2.41)**
-0.39
(2.79)**
Trade
-0.118
(1.41)
Monetary
-0.137
(2.03)*
Investment
-0.153
(2.04)*
Finance
-0.124
(1.32)
Prop. Rights
Corruption
Constant
Observations
R-squared
19.35
(0.80)
23
0.64
51.09
(2.02)*
23
0.70
39.88
(1.34)
23
0.60
43.24
(1.88)*
23
0.66
40.19
(1.58)
23
0.67
7.93
(0.37)
23
0.61
-0.113
(1.08)
16.71
(0.75)
23
0.58
Robust t statistics in parentheses
* significant at 5%; ** significant at 1%
Notes: FB is general government balance as percentage to GDP. For the other variables, see Table
10A. Notes.
the crisis (2008–2009), and before (1994–2007). The differences in coefficients
between Tables 1 and 4 are dramatic. Where trade and monetary freedoms were
associated with faster growth prior to the crisis, those countries which liberalized
most suffered the biggest declines in growth rates. Indeed, all measures of
economic freedom pick up negative and significant coefficients in Part A of
Table 4, which includes the size of the public sector.
Some studies of the size of government have found that open economies with
high terms of trade risk have significantly larger government consumption and
social security expenditures (Rodrik, 1998). Alesina and Wacziarg (1998) claim,
however, that the association between openness and government size is due to
the fact that smaller countries have both bigger public sectors and are more open
to trade. In a recent paper, Ram (2009) discusses both views and presents
evidence of a direct link between openness and government size. Our research on
transition countries suggests that large government expenditures might be a form
of insurance against adverse external shocks. While government size was seen to
be a drag on growth prior to the crisis, a large public sector tended to insulate
© 2012 Blackwell Publishing Ltd.
397
EVGENI PEEV/DENNIS C. MUELLER
transition countries from the adverse effects of the crisis. Economic liberalization and small public sectors led to more rapid growth in normal times, but free
markets and economic integration in the global economy made transition countries more vulnerable to the global financial crisis when it hit. The financial crisis
played havoc with many countries’ public finances and thus it is not surprising
that this variable becomes insignificant after the crisis hits.
VII. CONCLUSIONS
The collapse of the communist regimes in East Europe and the Soviet Union led
to the expectation for many in both the West and the East that democratic and
free market, capitalist institutions would take root in these countries. In the first
few years after the fall of communism, economic reforms were introduced in all
former communist countries, and political reforms to introduce democracy were
instituted in many. One might well have concluded that all former communist
countries were in transition toward liberal market economies, although at different speeds (Murrell, 2003). Given the well-established link between economic
and political freedoms, one might also have optimistically expected that economic liberalization would eventually lead to democracy in all transition countries. Such optimism is no longer possible. Today none of the former Soviet
Union countries has even moderately strong democratic institutions – with the
exception of the three Baltic States, Estonia, Latvia and Lithuania. The rose and
orange revolutions in Georgia and Ukraine raised hopes that they too might
someday join the Baltic countries in the (relatively) strong democratic category,
but that day still seems a long way off.
We believe that the development of strong democratic institutions and economic freedoms in the Baltic States despite their having been part of the Soviet
Union illustrates the importance of proximity to the European Union and the
attraction of membership in it for the transition process. Had the Baltic countries
been buried in Central Asia, like the Kyrgyz Republic, their first steps toward
democracy, like the Kyrgyz Republic’s promising first steps, might well have
faltered, and they too would have authoritarian regimes with weak economic
freedoms today. We cannot rule out the possibility, however, that the success of
the Baltic States was due to more favorable preconditions in these countries than
in the other FSU countries.
We have seen that there is a positive correlation between the strength of a
country’s democracy and the quality of its economic institutions. Economic
freedoms are stronger and corruption is weaker in former communist countries
with strong democratic institutions. This result could again merely reflect the
pull of membership in the European Union, which demands certain economic
freedoms and frowns upon corruption, but we think it is also partly due to the
effect of democracy on these institutional variables. Voters demand less corrup-
398
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DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
tion and greater economic freedoms and politicians respond to these demands in
countries with strong democratic institutions. This relationship can be easily
seen even within the countries, which have joined the European Union. Among
these, Bulgaria and Romania have the weakest democratic institutions, the
weakest economic freedoms, and the most corruption. In contrast, the three
Baltic countries score relatively high in both democracy and economic freedom.
This link between democracy and economic freedoms leads to a link between
democracy and economic growth, because economic liberalization produces
more rapid economic growth. We presented evidence that most economic
freedoms (but not all) produce more rapid growth. We identify trade freedom,
monetary freedom and freedom from corruption as the most important indicators
of economic freedom for growth in transition countries over the period 1994–
2007. Low corruption and external liberalization have been identified as positive
factors for economic growth in other studies (Mauro, 1995; Babecky and
Campos, 2011).34 Our study corroborates these findings. Economic freedoms
lead to higher growth rates in large part by stimulating investment, although
some economic freedoms (e.g., trade and monetary freedom, and freedom from
corruption) matter more for economic growth than others.
Democracy can have an adverse effect on economic growth, however, by
producing larger public sectors and public deficits, which lead to higher taxes
and a greater fiscal drag on the economy. Evidence of this relationship was also
presented. Democracy also seems to be associated with less labor market
freedom, which probably would also lead to slower growth, although we did not
have enough data to test for this relationship. Although the former communist
countries, which have become most democratic, have experienced higher levels
of growth, our results suggest that democracy also brings with it some institutional changes that retard growth.
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APPENDIX
Freedom House measures progress and setbacks in democratization in 29 countries and administrative areas from Central Europe to the Eurasian region of the
Former Soviet Union. It covers seven categories: electoral process; civil society;
independent media; national democratic governance; local democratic governance; judicial framework and independence; and corruption. Freedom House has
provided numerical ratings in the seven categories listed above and constructs
total index of democracy. The ratings are based on a scale of 1 to 7, with 1
representing the highest and 7 the lowest level of democratic progress.
Heritage Foundation measures several aspects of economic freedom in 183
countries. The indexes are based on a scale of 0 to 100, with 100 being the
highest level of economic freedom. We now briefly define the seven indexes of
economic freedom used in this study.35
Business freedom is the ability to create, operate, and close an enterprise
quickly and easily.
Trade freedom is a composite measure of the absence of tariff and non-tariff
barriers that affect imports and exports of goods and services.
Monetary freedom combines measures of price stability and price controls.
Property rights freedom is an assessment of the ability of individuals to
accumulate private property, secured by clear laws that are fully enforced by the
state.
Investment freedom is an assessment of the free flow of capital, especially
foreign capital.
Financial freedom is a measure of banking security as well as independence
from government control.
Freedom from corruption is based on quantitative data that assess the perception of corruption in the business environment.
35.
402
Full definitions are in Beach and Kane (2008).
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
The other data were obtained from various sources: Penn-World Table Version
6.3 (real GDP per capita, population); EBRD (general government expenditures
to GDP, fiscal balance to GDP, investment to GDP); World Bank (secondary and
tertiary education); Internet (distance from Brussels to capitals of transition
countries).
Table A1.
Initial Conditions
Country
CEE-5
Poland
Slovenia
Hungary
Czech Republic
Slovak Republic
SEE-5
Bulgaria
Romania
Croatia
Albania
The Macedonia
Baltic States
Estonia
Latvia
Lithuania
FSU
Russian Federation
Ukraine
Turkmenistan
Armenia
Belarus
Kazakhstan
Azerbaijan
Kyrgyz Republic
Georgia
Moldova
Tajikistan
Gcap
1990*
Gcap
1995
Sec
1990
Sec
1995
Ter
1990
7195
15125
11441
15097
12086
8308
15204
10491
14602
10004
81,5
91,1
78,6
91,2
96,3
90,5
97,8
98,7
93,7
22,1
24,6
14,4
16,7
2
2
2
3
2
6209
6922
10842
2805
7195
6415
6187
7976
2543
5956
75,2
92
69,2
37,5
55,7
78
77,9
81,8
70,2
60,9
31,7
9,6
21,9
15,4
16,8
1
1
1,5
1
1
9612
5918
7536
7706
6098
6898
98,5
91
91,7
103,7
85
84,2
26,8
25,5
34
2
2
2
13068
7732
10124
2833
9386
8421
4572
3494
3025
3090
2579
7895
5723
7131
3311
8339
7152
2563
2586
2895
2546
1664
93,3
92,8
85,7
92,6
115,3
80,2
93,4
84,4
76,8
78,8
75,6
80,9
80,6
53,3
48,1
22,1
1
1
0
0
1
0
0
0
1
0
0
95,3
97,5
87,5
100,1
94,9
80
102,1
51,3
41,6
23,9
14,9
37
35,9
22,8
ComLeg
1990
Notes: Gcap is real GDP per capita. Sec is secondary school enrollment percentage. Ter is tertiary
school enrollment percentage. ComLeg is the score for the communist legacies (Kitschelt, 1999).
*For the Baltic and FSU countries (except Estonia and the Russian Federation) the initial real GDP
per capita is for 1993.
Sources: Penn-World Table Version 6.3; World Bank.
© 2012 Blackwell Publishing Ltd.
403
EVGENI PEEV/DENNIS C. MUELLER
Table A2.
Democracy and Political Systems
Democracy Index
Country
CEE-5
Poland
Slovenia
Hungary
Czech Republic
Slovak Republic
SEE
Bulgaria
Romania
Croatia
Albania
Macedonia
Baltic States
Estonia
Latvia
Lithuania
FSU
Russia
Ukraine
Turkmenistan
Armenia
Belarus
Kazakhstan
Azerbaijan
Kyrgyz Republic
Georgia
Moldova
Tajikistan
Political Systems
1999
2007
Average 1999–2007
DPI
Political System
1,58
1,88
1,88
2,08
2,71
2,39
1,86
2,14
2,14
2,29
1,91
1,80
2,03
2,26
2,21
1,75
1,79
1,96
2,33
2,08
Parliamentary (rationalized)
Parliamentary (rationalized)
Pure parliamentary
Pure parliamentary
Pure parliamentary
3,58
3,54
4,46
2,86
3,36
3,64
3,20
3,51
3,78
3,38
3,63
3,79
4,75
3,83
3,82
3,86
4,13
4,00
4,17
4,29
Parliamentary
Semi-Presidential
Semi-Presidential (parlia.
with strong president)
Parliamentary
Parliamentary
2,25
2,29
2,29
1,93
2,07
2,25
2,01
2,17
2,21
2
2,25
2,13
Parliamentary
Parliamentary (rationalized)
Parliamentary-Presidential
4,58
4,63
6,75
4,79
6,25
5,5
5,58
5,08
4,17
4,25
5,75
5,96
4,25
6,93
5,21
6,71
6,39
6
5,93
4,79
5
6,07
5,32
4,56
6,88
5,01
6,53
6,12
5,74
5,57
4,67
4,74
5,78
4,96
4,71
6,83
4,92
6,46
6,17
5,46
5,67
4,83
4,71
5,63
Presidential-Parliamentary
Presidential-Parliamentary
Authoritarian Presidential
Presidential
Authoritarian Presidential
Close to Presidential
Presidential
Presidential-Parliamentary
Presidential
Parliamentary
Notes: The democracy ratings are based on a scale of 1 to 7, with 1 representing the highest level of
democratic progress and 7 the lowest.The Democracy Score is an average of ratings for Electoral
Process (EP); Civil Society (CS); Independent Media (IM); National Democratic Governance
(NGOV); Local Democratic Governance (LGOV); Judicial Framework and Independence (JFI); and
Corruption (CO). Source: Freedom House.
DPI System Score: Direct Presidential = 0; Strong President Elected by the Assembly = 1;
Parliamentary = 2. Source: Database on Political Institutions (DPI), see Beck et al. (2001).
Political system classification is from Metelska-Szaniawska (2009).
404
© 2012 Blackwell Publishing Ltd.
CEE-5
Poland
Slovenia
Hungary
Czech Republic
Slovak Republic
Average
SEE-5
Bulgaria
Romania
Croatia
Albania
The Macedonia
Average
Baltic States
Estonia
Latvia
Lithuania
Average
FSU
Russian Federat.
Ukraine
Turkmenistan
Armenia
Belarus
Kazakhstan
Azerbaijan
Kyrgyz Republic
Georgia
Moldova
Tajikistan
Average
Total average
© 2012 Blackwell Publishing Ltd.
67,53
74,07
58,10
55,59
65,09
64,08
84,47
74,33
83,22
80,67
52,83
44,35
30,00
81,28
58,64
56,53
61,60
60,40
85,01
68,46
43,40
58,41
63,96
55
55
55
70
85
70
70
75,00
85
55
55
55
70
55
40
55
55
70
55
59,09
64
.
58,75
54,05
73,04
73,94
63,87
69,30
66,84
2007
70
70
85
100
85
82
1994
Business
52
55
40
69
60
61
55
65
69
17,6
68,4
55,64
61,43
77
55
65
65,67
72,4
79
69
59
.
69,85
57
59
61
76
75
65,6
1994
86
86
86
86
86
86
2007
44,2
82,2
79,2
85
52,2
86,2
78,4
81,4
71
79,2
77,8
74,25
79,68
86
86
86
86,00
86
86
87,6
75,8
83,4
83,76
Trade
41,05
.
46,27
.
37,20
40,73
.
24,29
.
.
17,33
41,14
12,88
23,78
26,29
11,87
61,75
22,1
.
30,50
48,71
60,49
64,21
69,25
63,33
61,198
64,45
69,88
66,43
84,59
66,21
71,87
76,47
75,64
71,37
67,63
65,85
70,94
74,47
82,03
73,83
78,51
78,12
73,7
72,48
78,81
80,83
85,48
78,26
82,26
79,54
77,2
80,28
76,89
79,23
2007
Monetary
1994
Table A3.
70
50
30
30
50
30
10
50
50
30
30
39,09
50
90
50
50
63,33
.
65,00
70
70
50
70
70
30
70
70
70
62
1994
30
30
10
70
20
30
30
50
70
30
30
36,36
51,54
90
70
70
76,67
60
60
50
70
50
58,00
60
60
80
70
70
68
2007
Investment
Economic Freedom
50
50
10
50
50
30
30
50
30
10
30
35,45
42,8
70
50
30
50,00
.
50,00
50
50
50
50
50
70
50
90
50
62
1994
40
50
10
70
10
60
30
50
60
50
40
42,73
54,62
80
70
80
76,67
60
50
60
70
60
60,00
60
50
70
80
80
68
2007
Finance
50
30
30
50
50
30
30
30
30
50
30
37,27
43,6
70
50
50
56,67
.
45,00
50
30
50
50
50
30
70
70
70
58
1994
30
30
10
35
20
30
30
30
35
50
30
30,00
38,65
90
55
50
65,00
30
30
30
30
30
30,00
50
50
70
70
50
58
2007
Property Rights
10
10
10
50
10
10
10
30
10
10
10
15,45
25,2
50
50
30
43,33
.
20,00
30
10
30
10
50
30
50
50
50
46
1994
25
28
22
29
21
26
24
22
28
32
22
25,36
34,5
67
47
48
54,00
40
31
34
26
27
31,60
37
64
52
48
47
49,6
2007
Corruption
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
405
EVGENI PEEV/DENNIS C. MUELLER
Table A4.
Public Sector Size and Economic Growth
Country
CEE-5
Poland
Slovenia
Hungary
Czech Republic
Slovak Republic
SEE-5
Bulgaria
Romania
Croatia
Albania
The Macedonia
Baltic States
Estonia
Latvia
Lithuania
FSU
Russian Federation
Ukraine
Turkmenistan
Armenia
Belarus
Kazakhstan
Azerbaijan
Kyrgyz Republic
Georgia
Moldova
Tajikistan
Government
Expenditure
1995
Government
Expenditure
2007
Fiscal
Balance
1995
Fiscal
Balance
2007
Gcap
2007/95
Gcap
2004/95
50,15
41,59
52,63
40,49
54,09
42,1
42,3
49
42,6
34,4
-3,1
0,04
-6,72
-1,06
0,4
-1,9
0,5
-4,9
-0,6
-1,9
1,74
1,72
1,63
1,50
1,73
1,47
1,45
1,48
1,25
1,39
41,31
34,74
48,93
33,44
38,95
37,2
34,5
42,8
29,1
33,1
-5,63
-2,5
-0,71
-10,06
-1,05
3,5
-3,1
-2,5
-3,5
0,6
1,50
1,50
1,73
1,86
1,16
1,25
1,27
1,46
1,58
1,06
39,43
37,48
34,68
34,8
35,9
34,8
-1,19
-3,57
-4,22
2,6
-0,4
-1
2,45
2,44
2,11
1,85
1,79
1,68
43,35
42,53
20,14
28,85
42,47
20,82
21,13
33,19
12,33
46,19
24,41
34,4
43,8
13,4
22,4
49
23
27,4
28
20
41,5
28,6
-6,61
-4,71
0,38
-8,97
-2,7
-3,35
-3,13
-17,3
-5,27
-6,74
-6,07
6
-2
4
-2,3
0,4
4,7
2,4
-0,3
-4,2
-0,3
-6,2
1,70
1,72
1,60
2,88
2,70
2,10
4,01
1,38
3,07
1,37
1,70
1,38
1,44
1,27
2,03
1,99
1,66
1,82
1,46
2,02
1,22
1,50
Notes: Government expenditures are general government expenditures as percentage to GDP. Fiscal
balance is general government balance as percentage to GDP. Gcap is real GDP per capita.
Source: EBRD.
406
© 2012 Blackwell Publishing Ltd.
DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES
Table A5.
Correlations Between Democracy and Economic Freedom
Demo
Demo
Business
Trade
Monetary
Investment
Finance
Property Rights
Corruption
Gov. Expenditure
Fiscal Balance
Business
1.0000
-0.7051* 1.0000
-0.4237* 0.3033*
-0.4577* 0.2670*
-0.7811* 0.6712*
-0.7178* 0.5762*
-0.7602* 0.6371*
-0.7554* 0.5622*
-0.5546* 0.3327*
0.2154* -0.0106
Property Rights
Corruption
Gov. Expenditure
Fiscal Balance
Trade
1.0000
0.5436*
0.3253*
0.4491*
0.2475*
0.3917*
0.0688
0.1298
Monetary Investment Finance Property Rights
1.0000
0.3008*
0.4993*
0.1794*
0.3820*
0.0560
0.1977
1.0000
0.7126* 1.0000
0.6871* 0.6311*
0.6049* 0.6020*
0.3328* 0.3548*
-0.1471* -0.0282
1.0000
0.7053*
0.4661*
-0.0921
Corruption
Gov. Expenditure
Fiscal Balance
1.0000
0.5812*
0.0984
1.0000
-0.3034*
1.0000
* significant at 1%
Notes: Demo is the Freedom House total democracy score. The economic freedom indexes of the
Heritage Foundation are: Business, Trade, Monetary, Investment, Finance, Property Rights, Corruption. See Appendix, for definitions of these variables. Government expenditures are general government expenditures as percentage to GDP. Fiscal balance is general government balance as percentage
to GDP.
Sources: Freedom House; Heritage Foundation; EBRD.
SUMMARY
This article examines the interrelationships between democracy, economic freedoms, and economic growth.
We study 24 post-communist economies over the period 1990–2007, and find that strong democratic
institutions are associated with greater economic freedoms and larger public sectors and public deficits.
Stronger economic freedoms lead to more rapid growth, but large public sectors and public deficits have
adverse effects on growth. We identify trade freedom, monetary freedom and freedom from corruption as the
most important indicators of economic freedom for growth in transition countries over the period 1994–
2007. Some of the factors associated with faster growth prior to the crisis were associated with greater
declines in growth during the first years of the financial crisis (2008–2009).
© 2012 Blackwell Publishing Ltd.
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