Democracy Ec Freedom Trans Econ Peev Kyklos2012

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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 com-

pleted, 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 formermembers 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 bymarket reforms and has led to more rapid growth in transition countries.

A large literature in political science links democracy to various socio-

economic 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 Autnoma de Barcelona and

EAIRE 36th Annual Conference in Ljubljana. We wish to thank theAustrian National Bank for financial

support under the Jubilumsfondsproject Nr. 12325 and the FWF project P 19522-G14.

KYKLOS, Vol. 65 August 2012 No. 3, 371407

2012 Blackwell Publishing Ltd., 9600 Garsington Road,

Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA 371


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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 todemocratize 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 alloca-

tion 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 liberaliza-

tion of economic activity, and (2) changes in government expenditures, transfers

and taxes. We treat both dimensions separately and propose and test hypothesesabout 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

countrys 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, Lopez-

de-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 countrysstocks 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 eco-

nomic 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, Lundstrm and Sturm (2006).

2. There are few exceptions. See, Justesen (2008).

EVGENI PEEV/DENNIS C. MUELLER

372 2012 Blackwell Publishing Ltd.


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mixes different aspects of reform such as large- and small-scale privatization,

governance and enterprise restructuring, price liberalization, trade and foreign-

exchange liberalization, competition policy, and banking and securities markets

reform.3 As Heckelman and Stroup (2005) show, however, these aggregationshave 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 divid-

ing 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 economicreform 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 thearticle is to examine the effects of economic freedoms, public expenditures and

fiscal balance on growth in transition countries over the period 19942007, and

following the financial crisis (20082009).

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 happenedsince 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.

DEMOCRACY, ECONOMIC FREEDOM AND GROWTH IN TRANSITION ECONOMIES

2012 Blackwell Publishing Ltd. 373


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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 commu-

nism, 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 Kitschelts evaluation of the communist bureaucracies

whether they were professional or relied on patronage, or patrimonial. The

higher the score, the better suited a countrys 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 coun-

tries (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 geog-

raphy and political history in common. The two richest transition countries in

CEE in 1990 were Slovenia and the Czech Republic. The three Baltic coun-

tries 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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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 homog-

enous within groups, and differ greatly across groups. The five CEE countriesreceive 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, accord-

ing 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 countrys democratic institutions, we use Freedom

Houses Index of Democracy. Freedom House has covered transition countries in

two publications: Freedom in the Worldreporting annually two indicators (politi-

cal rights and civil liberties scores) and Nations in Transit, a comprehensive

survey of reforms in transition countries since 199495. While the former pub-

lication is useful for comparative studies between established democracies andpost-communist countries, the latter presents a more comprehensive picture of

post-communist transition focusing on seven dimensions of democratic institu-

tions.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 demo-

cratic institutions. The first three columns of Table A2 present the values for

1999, 2007 and the average for the period 19992007 (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 thatdemocracy 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. Slovakias 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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countries. The high democracy scores for the CEE countries are in line with

Kitschelts 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 Kitschelts

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 ahigher 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, transi-

tion countries could select between a parliamentary system with weak or non-

existent president, a strong presidential system, or something in between. The

last two columns of Table A2 report transition countries scores for system ofgovernment from the World Banks 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 countrys constitution. The two classifications are in substantial

agreement. The simple correlation between the DPI system score and the democ-

racy 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 authoritari-

anism, and parliamentary systems with strong democratic institutions. This neednot 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 coun-

tries 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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3. Economic freedom

Economic freedoms were, of course, severely restricted under communism and

at the start of the transition process. As with democratic institutions, economicfreedoms 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 Foun-

dation. Many studies use instead the index of economic freedom of the Fraser

Institute. For our purposes, the Heritage Foundation indexes have some advan-

tages 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 coun-

tries over this time period, annual data are a great advantage. The HeritageFoundation 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., theBaltic States and CEE countries). Theyare more suitable for distinguish-ing 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 elements marginal effect on growth. We thus keep the indi-

vidual 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 determi-

nant of economic growth, but treat it as a separate variable rather than as a

10. 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).

11. For a survey see De Haan, Lundstrm and Sturm, 2006).




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component of economic freedom. Table A3 reports the first values of the meas-

ures 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 until1989 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 havedeclined in Russia over the time period for most measures of economic freedom.

4. Public sector size

As noted in theprevious subsection, government size is treated as a separate factor

affecting economic growth. Table A4 presents EBRD figures for general govern-

ment 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

tobeclose toone at the start of the periodand decline over time. The EBRD countsas 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 publicsectors 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 countrys




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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 indi-

cate 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 andreached 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 devel-

oping 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 estab-

lished governments in TEs (transition economies), especially during the transi-

tion 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 combi-

nation 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 differ-

ence is readily apparent in Tables A2 and A3. Moreover, the data in these tables

indicate that some transition countries have succeeded in overcoming the disad-

vantages that they inherited from communism, and have developed rather gooddemocratic 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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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 democratiza-

tion in the transition countries their distance from the European Union. We thusconstruct a third variable, Dist, the distance of a countrys 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 coeffi-

cients 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 resultsare as follows (t-statistics below the coefficients).15

Dem t Y t Y t EdTert = + + 3 98 0 14 0 012 0 01814 56

907 96

290

5 75

. . . .. . .

9904 48

290

2 61 10 96

2

0 0015 0 00033

0 00003

.

. .. .

.

+

t EdTer t Dist

t DDist N R6 92

2216 0 67.

, , . .= =

Recalling that higher democracy scores mean weaker democracy, we expectnegative 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 notperform 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, sowe 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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countries (see again, Glaeser, La Porta, Lopez-de-Silanes and Shleifer, 2004).

(Educations 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 t2Y90 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 EuropeanUnion 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 prox-

imity to Russia hindered democratization.

As discussed above, Kitschelt (1999) attributes the institutional choices of

transition countries to structural factors and bureaucratic legacies present before

communisms demise. To test this hypothesis, we addthevariable, ComLeg,totheabove 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 Kitschelts

ComLeg scores. Thus, each is likely to detract from the explanatory power of theother. Once again we allow the effect ofComLeg on democracy to vary over time.

Dem t Y t EdTert = + +3 91 0 004 0 014 0 001116 48

900 60

903 99

. . . .. . .

tt EdTer

t Dist E t Dist t

290

2 28

3 67

06 2

2 200 00010 7 9 0 49

+

.

. .. . .

+ = =

ComLeg

t ComLeg N R8 83

2

6 30

20 042 216 0 79.

.

. , , .

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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Thus, the different legacies from the communist era had a more pronouncedeffect 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

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.

(1) (2) (3) (4) (5) (6) (7)

GE -0.164 -0.147 -0.122 -0.172 -0.170 -0.158 -0.22(3.56)** (3.32)** (2.83)** (3.75)** (3.78)** (3.38)** (4.46)**

GDP 2.13 1.648 0.647 2.08 1.90 2.206 1.158(2.42)** (1.97)* (0.77) (2.45)** (2.22)* (2.53)** (1.35)

INV 0.173 0.162 0.148 0.177 0.176 0.178 0.165(2.15)* (2.10)* (1.94)* (2.28)* (2.25)* (2.26)* (2.12)*

GPO -41.165 -28.78 -63.01 -28.44 -32.23 -45.37 -19.90(0.60) (0.44) (0.97) (0.42) (0.48) (0.65) (0.30)

Business 0.014(0.42)

Trade 0.126(2.90)**

Monetary 0.108(4.06)**

Investment 0.029(1.18)

Finance 0.029(1.41)

Prop. Rights -0.005(0.25)

Corruption 0.118(2.76)**

Constant -13.49 -17.55 -7.07 -13.48 -11.95 -13.37 -5.519(1.99)* (2.57)** (1.10) (1.99)* (1.78)* (1.97)* (0.80)

Observations 322 322 322 322 322 322 322

R-squared 0.08 0.12 0.16 0.09 0.09 0.08 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 toGDP. GPO is growth in population. Subscript c stands for country and t for year.Sources: Penn-World Table Version 6.3; EBRD; Heritage Foundation.




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history in the form of a countrys communist legacy, and the future in the form

of expectations (hopes) of entering the European Union help explain the adop-

tion 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 liberal-

ism. 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 econo-mies are paired with closed political systems. Throughout history most countries

16. Friedman (1962), Bobbio (1990), and Diamond 1995).

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.

(1) (2) (3) (4) (5) (6) (7)

FB 0.669 0.631 0.598 0.709 0.683 0.656 0.683(5.98)** (6.15)** (5.95)** (6.05)** (6.01)** (5.67)** (6.17)**

GDP -0.576 -0.746 -1.46 -0.799 -0.892 -0.408 -1.40(0.76) (1.01) (2.01)* (1.13) (1.22) (0.54) (1.71)*

INV 0.10 0.097 0.084 0.106 0.107 0.111 0.104(1.27) (1.30) (1.13) (1.39) (1.40) (1.45) (1.36)

GPO -13.76 -6.545 -43.295 -7.01 -3.922 -18.61 -1.52(0.21) (0.10) (0.68) (0.10) (0.06) (0.28) (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)


Constant 7.50 1.97 10.70 8.906 10.09 7.45 14.37(1.23) (0.32) (1.82)* (1.51) (1.66)* (1.20) (2.14)*

Observations 322 322 322 322 322 322 322

R-squared 0.14 0.18 0.22 0.15 0.15 0.14 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.




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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 econo-mies, are fairly new on the worlds stage.

All of the countries examined in this study were dictatorships with closed

economies until 1989 or 1991. In the early transition years, rapid democratiza-

tion 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 eco-nomic 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 areopen 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 presiden-

tial systems in the transition countries. Persson and Tabellini (2000, 2003) have

developed a model, which predicts large public sectors in multiparty parliamen-

tary systems, because of the need to form broad coalitions of interests in these

systems. They predict and find smaller public sectors in countries with presiden-

tial systems than in multiparty parliamentary systems. The correlation between

17. See, Fidrmuc (2003).

18. See, de Melo, Denizer and Gelb (1996), Dethier et al. (1999), and Fish (2003).




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democracy and state spending in the transition countries might be due to the fact

that the countries with strong democratic institutions overwhelmingly have mul-

tiparty parliamentary systems. The Persson and Tabellini model, however,

assumes that political competition also exists in presidential systems. This is notthe 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 con-

ditions 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 EF0is 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, theyestimate 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 countrys 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. 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, Lundstm and Sturm (2006).

20. See discussion in De Haan, Lundstm and Sturm (2006).




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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), muchlarger 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 theright-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 tran-

sition 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 relationshipbetween 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 lookat 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, Lundstm 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. 54854).25. See e.g. Chu Ke-young and Gerd Schwartz (1994), Kornai (1995), Coricelli (1997), and Dabrowski

(1997).

26. See, Beck and Laeven (2005).




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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 linkbetween 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 publics 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 authori-

tarianism 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 publicsectors 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 asso-

ciation with economic growth.

Democracy Large Budget Deficits Slow Economic Growth

We test these hypotheses by regressing country growth rates on various meas-

ures of public sector size and economic freedoms. In doing so, we treat democ-

racy as a latent variable explaining both public sector size and economic

freedoms. In the regressions to explain economic growth, we also include stand-

ard control variables from the growth literature total capital investment as a

27. See, Pushak et al (2007).




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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 countrys 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 subsequentgrowth rates in transition countries. Indeed, their coefficients are typically

negative and often statistically significant, when added to the growth equa-

tions. 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 posi-

tive signs, with three of the seven (trade freedom, monetary freedom andfreedom 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 coeffi-

cients 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.




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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 govern-ment. 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 defi-

cits) 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 laggeddeviations 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 vari-

ables 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 sur-pluses). We attempted to test for this possibility by estimating a two equation,

three-stage-least-squares model with growth and budget surpluses as endog-

enous 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 cross-

national 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 ofgovernment size and significant positive effects of investment on growth (see e.g. Campos, 2001;

Fidrmuc, 2003).

31. See, Temple (2000).




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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 govern-

ment size in the regressions, the coefficients on trade freedom, monetary freedomand 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 countrys

annual growth by two percentage points. A reduction of the budget deficit by one

percent of GDP increases a countrys growth rate by slightly more than 0.8percentage 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 equa-

tions. 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 thetransition countries. Yet its dummy variable is generally insignificant. Estonias

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 liber-

alize 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




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Table 2.

Part A. Economic Freedoms, Government Expenditures and Growth (Fixed Effects)

(1) (2) (3) (4) (5) (6) (7)

GE -0.236 -0.189 -0.124 -0.241 -0.247 -0.223 -0.282(2.92)** (2.33)** (1.57) (2.99)** (3.02)** (2.78)** (3.53)**

GDP 3.27 0.519 -4.54 3.25 3.62 2.27 2.13(1.63) (0.24) (1.92)* (1.62) (1.75)* (1.10) (1.07)

INV 0.143 0.153 0.136 0.142 0.142 0.145 0.111(1.69)* (1.85)* (1.70)* (1.69)* (1.69)* (1.74)* (1.34)

GPO 369.44 381.20 338.65 370.39 377.10 393.85 372.92(3.10)** (3.26)** (3.00)** (3.11)** (3.14)** (3.31)** (3.21)**

Albania 0.397 -0.509 -6.28 0.69 0.45 -1.54 2.18(0.15) (0.19) (2.25)* (0.26) (0.17) (0.54) (0.83)

Belarus 3.75 5.62 12.28 3.55 3.47 3.10 5.91(1.51) (2.31)* (4.51)** (1.40) (1.37) (1.28) (2.44)**

Armenia 5.54 3.92 1.68 5.56 5.99 5.94 4.51(2.51)** (1.75)* (0.76) (2.52)** (2.56)** (2.69)** (2.06)*

Azerbaijan -1.68 -2.02 -4.67 -2.13 -1.96 -3.69 -0.156(0.59) (0.74) (1.74)* (0.69) (0.68) (1.23) (0.06)

Georgia 4.84 4.44 2.13 4.76 4.73 3.43 6.44(1.93)* (1.79)* (0.87) (1.89)* (1.88)* (1.31) (2.57)**

Croatia 1.84 2.28 1.51 2.01 2.11 0.79 1.61(0.79) (1.02) (0.70) (0.89) (0.93) (0.34) (0.72)

Slovak Rep. 0.262 -0.0005 1.13 0.44 0.37 1.37 -0.67(0.11) (0.01) (0.51) (0.19) (0.16) (0.57) (0.30)

Poland 1.42 1.66 2.18 1.59 1.43 3.73 -0.57(0.66) (0.79) (1.07) (0.79) (0.67) (1.50) (0.26)

Lithuania -0.072 -0.73 1.08 0.031 -0.15 0.85 -1.45(0.04) (0.40) (0.61) (0.02) (0.08) (0.40) (0.78)

Latvia 4.82 4.11 3.78 4.99 5.02 5.85 4.13(2.18)* (1.96)* (1.86)* (2.21)* (2.25)* (2.64)** (1.98)*

Estonia 3.98 3.00 5.30 4.39 4.13 7.65 -0.83(1.55) (1.34) (2.44)** (1.55) (1.69)* (2.41)** (0.33)

Kazakhstan -2.57 -0.489 0.84 -3.04 -2.96 -3.48 -0.25(1.15) (0.21) (0.38) (1.22) (1.26) (1.53) (0.11)

Kyrgyz Rep. -6.98 -8.64 -11.64 -7.02 -6.79 -9.40 -6.91(2.34)** (2.91)** (3.96)** (2.36)** (2.31)* (2.89)** (2.39)**

Macedonia -3.49 -3.26 -7.99 -3.45 -3.03 -5.13 -3.01(1.33) (1.27) (3.06)** (1.32) (1.13) (1.86)* (1.18)

Romania -0.87 -1.05 1.39 -0.73 -0.89 -2.35 -0.62

(0.49) (0.60) (0.77) (0.41) (0.50) (1.20) (0.36)Turkmenistan -11.76 -8.85 -5.83 -12.16 -12.77 -13.86 -8.11(3.93)** (3.30)** (2.03)* (3.80)** (3.56)** (4.46)** (2.77)**

Tajikistan -8.34 -11.11 -12.79 -8.73 -8.55 -11.22 -6.75(1.96)* (2.61)** (3.13)** (1.98)* (2.01)* (2.49)** (1.64)

Moldova 0.66 -2.48 -5.40 0.41 0.91 0.48 0.84(0.25) (0.89) (1.99)* (0.16) (0.34) (0.19) (0.33)

Bulgaria 3.84 4.61 4.61 4.13 4.13 4.06 3.33(1.82)* (2.21)* (2.29)* (1.90)* (1.92)* (1.93)* (1.61)

Czech Rep. -2.14 -1.49 0.35 -2.01 -1.81 1.44 -3.65(0.82) (0.61) (0.15) (0.77) (0.68) (0.44) (1.45)

Russ. Fed. 1.62 2.14 3.04 1.93 1.78 5.08 -0.61(0.62) (0.84) (1.23) (0.70) (0.68) (1.57) (0.24)

Hungary -0.68 2.04 3.31 -0.718 -0.86 -0.70 1.11(0.36) (0.97) (1.68) (0.37) (0.44) (0.37) (0.57)

Slovenia -1.01 1.12 3.57 -1.17 -1.38 0.69 -3.63(0.36) (0.40) (1.31) (0.43) (0.51) (0.24) (1.32)

Ukraine 3.34 3.22 2.67 3.31 3.38 2.20 4.81(1.58) (1.59) (1.36) (1.58) (1.64) (1.02) (2.34)**

Business -0.019(0.35)Trade 0.137

(2.98)**Monetary 0.168

(5.60)**Investment -0.021

(0.49)Finance -0.022

(0.61)Prop.Rights -0.118

(1.83)*Corruption 0.192

(3.53)**Constant -17.91 -6.27 35.73 -17.62 -20.57 -5.65 -12.78

(1.00) (0.35) (1.84)* (0.99) (1.16) (0.30) (0.74)Obs 322 322 322 322 322 322 322R-squared 0.19 0.22 0.20 0.19 0.19 0.20 0.23

Absolute value of t statistics in parentheses* significant at 5%; ** significant at 1%

Notes: See Table 7A. Notes.




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Table 2.

Part B. Economic Freedoms, Fiscal Balance and Growth (Fixed Effects)

(1) (2) (3) (4) (5) (6) (7)

FB 0.879 0.828 0.684 0.889 0.88 0.855 0.856(6.77)** (6.43)** (5.13)** (6.83)** (6.81)** (6.52)** (6.68)**

GDP 0.32 -1.98 -5.10 0.325 0.408 -0.155 -0.309(0.17) (0.95) (2.25)* (0.17) (0.20) (0.08) (0.16)

INV 0.044 0.066 0.067 0.039 0.044 0.05 0.019(0.54) (0.84) (0.88) (0.50) (0.55) (0.63) (0.24)

GPO 220.71 240.73 229.79 211.56 223.25 240.26 233.33(1.92)* (2.13)* (2.07)* (1.84)* (1.93)* (2.08)* (2.06)*

Albania 4.47 3.24 -1.79 4.17 4.50 3.27 5.91(1.81)* (1.31) (0.64) (1.65)* (1.82)* (1.21) (2.37)**

Belarus 1.06 3.02 8.48 1.59 0.949 0.711 2.13(0.49) (1.38) (3.20)** (0.70) (0.42) (0.33) (1.01)

Armenia 7.79 5.89 3.91 7.70 7.93 7.94 7.49(4.18)** (3.01)** (1.94)* (4.12)** (3.86)** (4.26)** (4.06)**

Azerbaijan 0.28 -0.69 -3.03 1.02 0.217 -0.998 1.73(0.11) (0.29) (1.24) (0.38) (0.09) (0.37) (0.71)

Georgia 6.40 5.49 3.41 6.38 6.42 5.57 8.18(3.15)** (2.70)** (1.63) (3.14)** (3.16)** (2.56)** (3.87)**

Croatia 0.86 1.59 1.23 0.95 0.87 0.255 0.076(0.45) (0.85) (0.68) (0.51) (0.46) (0.13) (0.04)

Slovak Rep. 0.22 0.48 1.43 -0.029 0.227 0.898 -0.940(0.11) (0.25) (0.75) (0.01) (0.12) (0.44) (0.47)

Poland 0.82 1.43 1.94 0.589 0.812 2.16 -0.958(0.43) (0.77) (1.06) (0.31) (0.43) (0.96) (0.49)

Lithuania 0.032 -0.436 0.95 -0.36 0.048 0.634 0.773(0.02) (0.25) (0.55) (0.19) (0.03) (0.34) (0.44)

Latvia 2.84 2.49 2.58 2.36 2.91 3.56 2.53(1.35) (1.25) (1.32) (1.09) (1.38) (1.67)* (1.26)

Estonia 0.76 0.40 2.68 -0.26 0.857 3.06 -2.33(0.31) (0.19) (1.24) (0.10) (0.37) (0.99) (0.96)

Kazakhstan -1.05 0.22 0.72 -0.48 -1.12 -1.65 1.03(0.57) (0.12) (0.39) (0.24) (0.59) (0.86) (0.52)

Kyrgyz Rep. -2.42 -4.40 -7.28 -2.15 -2.39 -3.97 -2.37(0.85) (1.55) (2.48)** (0.76) (0.86) (1.26) (0.86)

Macedonia -5.26 -4.97 -8.29 -5.19 -5.18 -6.16 -5.02(2.13)* (2.05)* (3.33)** (2.11)* (2.06)* (2.37)** (2.06)*

Romania -0.87 -1.13 0.80 -0.97 -0.878 -1.71 -0.63

(0.52) (0.69) (0.47) (0.58) (0.52) (0.92) (0.38)Turkmenistan -7.39 -5.79 -4.50 -6.57 -7.64 -8.84 -4.52(2.82)** (2.37)** (1.85)* (2.38)** (2.52)** (3.18)** (1.73)*

Tajikistan -5.35 -8.53 -10.04 -4.63 -5.40 -7.15 -3.89(1.37) (2.17)* (2.60)** (1.16) (1.40) (1.71)* (1.02)

Moldova -2.46 -4.99 -6.40 -2.19 -2.42 -2.48 -2.27(0.99) (1.90)* (2.47)** (0.87) (0.96) (1.00) (0.92)

Bulgaria -0.96 0.04 0.77 -1.30 -0.912 -0.722 -1.31(0.47) (0.02) (0.38) (0.61) (0.43) (0.35) (0.64)

Czech Rep. -1.06 -0.08 1.06 -1.48 -0.968 1.02 -2.50(0.44) (0.04) (0.47) (0.62) (0.40) (0.34) (1.06)

Russ. Fed. 2.13 3.16 3.75 1.69 2.16 4.12 -0.023(0.95) (1.45) (1.75)* (0.74) (0.98) (1.43) (0.01)

Hungary -3.25 -0.663 0.469 -3.17 -3.31 -3.20 -2.03(1.78)* (0.33) (0.24) (1.73)* (1.77)* (1.75)* (1.09)

Slovenia -1.79 0.62 2.40 -1.83 -1.87 -0.708 -3.95(0.71) (0.24) (0.94) (0.76) (0.76) (0.27) (1.55)

Ukraine 0.33 0.40 0.55 0.31 0.314 -0.272 1.22(0.17) (0.21) (0.30) (0.16) (0.16) (0.13) (0.63)

Business -0.002(0.03)Trade 0.119

(2.78)**Monetary 0.129

(4.35)**Investment 0.024

(0.59)Finance -0.005

(0.15)Prop.Rights -0.065

(1.06)Corruption 0.138

(2.68)**Constant 3.665 14.95 42.42 3.12 3.12 10.44 5.33

(0.21) (0.87) (2.27)* (0.18) (0.18) (0.58) (0.32)Obs 322 322 322 322 322 322 322R-squared 0.28 0.30 0.33 0.28 0.28 0.29 0.30

Absolute value of t statistics in parentheses* significant at 5%; ** significant at 1%

Notes: See Table 7B. Notes.




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possible candidates for explaining growth. With country effects accounted for,

government size and fiscal balance continue to have highly significant relation-

ships to economic growth. The fact that the strength of democratic institutions is

strongly associated with larger government sectors and bigger government defi-cits 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. Oneway to adjust for this would be to choose instruments to estimate investment.

Obvious choices wouldbe initial incomeandeducationlevels,but these also affect

the other variables in the model. We have chosen, therefore, to check for the

possibility of investments 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 omis-

sion 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 prop-

erty rights freedom have in both the equations insignificant coefficients.

The Heritage Foundations 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 andfreedom 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 nowattempt to isolate any joint impacts that they might have.

32. See definitions in the Appendix, and discussion in Heckelman and Stroup (2005).




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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 relation-

ships best describes the data by experimenting with various multiplicative and

additive combinations of the variables. The additive formulations always exhib-

ited 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 equa-

tion was (t-statistics under coefficients).

G GE GDP Invct ct**

ct t= + +11 31 0 19 1 04 0 151 59 4 08

11 21 2 0

. . . .. . . . 33 0 23 2 41

2 66

15 20 0 10

0 08

* **

**

PopGr Trade

Corruption N

+

+ =

. .

. ,. .

.

3322 0 132, . .Adj R =

With fiscal balance as the measure of government size, the best fit equations

included trade freedom and either finance freedom or freedom from corruption

Table 3.

Part A. Economic Freedoms, Size of Government and Growth

(1) (2) (3) (4) (5) (6) (7)

GE -0.167 -0.148 -0.125 -0.173 -0.175 -0.163 -0.234(3.41)** (3.20)** (2.74)** (3.56)** (3.76)** (3.24)** (4.64)**

GDP 2.29 1.883 0.787 2.38 2.12 2.47 1.17(2.55)** (2.17)* (0.89) (2.76)** (2.35)** (2.81)** (1.26)

GPO -57.87 -35.82 -70.63 -45.73 -44.12 -61.67 -29.77(0.79) (0.53) (1.07) (0.63) (0.62) (0.83) (0.43)


Trade 0.159(3.57)**

Monetary 0.126(4.74)**

Investment 0.034(1.38)

Finance 0.043(1.99)*



Constant -12.50 -18.05 -5.893 -12.29 -10.32 -11.93 -2.33(1.78)* (2.68)** (0.88) (1.75)* (1.46) (1.69)* (0.31)

Observations 328 328 328 328 328 328 328R-squared 0.05 0.11 0.15 0.06 0.06 0.05 0.10


Notes: See Table 7A. Notes.




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(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 eco-

nomic 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

Table 3.


(1) (2) (3) (4) (5) (6) (7)

FB 0.708 0.660 0.625 0.75 0.729 0.701 0.725(6.19)** (6.18)** (6.00)** (6.38)** (6.38)** (5.92)** (6.49)**

GDP -0.729 -0.793 -1.593 -0.842 -1.04 -0.509 -1.757(0.97) (1.13) (2.24)* (1.24) (1.39) (0.69) (2.03)*

GPO -40.09 -22.94 -60.09 -18.04 -23.16 -42.97 -18.43(0.56) (0.35) (0.93) (0.25) (0.34) (0.59) (0.27)


Trade 0.154(3.65)**

Monetary 0.122(4.90)**

Investment 0.054(2.18)*

Finance 0.051(2.38)**



Constant 9.88 2.72 12.87 11.41 13.27 10.44 19.07(1.57) (0.44) (2.13)* (1.87)* (2.07)* (1.63) (2.68)**



Notes: See Table 7B. Notes.




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positive link between economic freedom and economic growth does not disap-

pear, 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 equa-

tions using the same explanatory variables as were used in Table 1. The depend-ent variable, however, is now the difference between a countrys growth rate after

33. These results are available on request.

Table 4.

Part A. Government Expenditures and Growth

(1) (2) (3) (4) (5) (6) (7)

GE 0.26 0.287 0.244 0.268 0.286 0.316 0.333(2.90)** (3.14)** (2.21)* (3.17)** (3.93)** (3.39)** (3.65)**

GDP -2.00 -4.47 -4.54 -5.80 -4.65 -0.973 -1.16(0.81) (1.40) (1.63) (2.84)** (2.25)* (0.60) (0.44)

INV 0.13 0.065 0.44 0.66 0.046 0.101 0.101(0.60) (0.41) (0.16) (0.32) (0.24) (0.48) (0.44)

GPO 457.09 403.06 449.96 296.94 320.06 519.94 -19.90(2.44)** (3.14)** (2.17)* (1.59) (1.79)* (3.37)** (0.30)

GDP Growth -0.48 -0.17 -0.537 -0.44 -0.457 -0.553 -0.560(1.34) (0.74) (1.32) (1.41) (1.61) (1.59) (1.50)

Business -0.244(-2.34)**

Trade -0.429(4.58)**

Monetary -0.128(1.91)*

Investment -0.148(3.18)**

Finance -0.176(2.95)**

Prop. Rights -0.17(2.71)**

Corruption -0.192(2.41)**

Constant 13.75 50.47 31.41 41.58 34.80 -5.06 -4.41(0.65) (1.77)* (1.26) (2.10)* (1.68)* (0.40) (0.20)


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 20082009 and19942007. GDP growth is the average growth rate over the period 19942007. GDP is the logarithmof real GDP per capita in 1990. The other independent variables are averages over the period19942007. For the other variables definitions see Table 7A. Notes.




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the crisis (20082009), and before (19942007). 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 ofTable 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

Table 4.


(1) (2) (3) (4) (5) (6) (7)

FB 0.013 -0.046 0.138 -0.038 0.067 0.047 0.201(0.04) (0.16) (0.43) (0.11) (0.20) (0.15) (0.72)

GDP -1.33 -3.32 -4.08 -4.64 -3.81 -0.911 -1.88(0.43) (1.20) (1.28) (1.91)* (1.55) (0.36) (0.66)

INV 0.132 0.092 0.015 0.090 0.037 0.100 0.055(0.45) (0.35) (0.05) (0.31) (0.13) (0.33) (0.17)

GPO 288.35 222.92 293.54 135.48 157.46 321.28 293.21(1.74)* (1.81)* (1.74)* (0.74) (0.91) (2.35)** (1.74)*

GDP Growth -0.930 -0.690 -0.940 -0.905 -0.940 -1.05 -1.04(2.28)* (1.87)* (2.29)* (2.24)* (2.65)** (2.57)** (2.41)**

Business -0.222(1.64)

Trade -0.39(2.79)**

Monetary -0.118(1.41)

Investment -0.137(2.03)*

Finance -0.153(2.04)*

Prop. Rights -0.124(1.32)

Corruption -0.113(1.08)

Constant 19.35 51.09 39.88 43.24 40.19 7.93 16.71(0.80) (2.02)* (1.34) (1.88)* (1.58) (0.37) (0.75)



Notes: FB is general government balance as percentage to GDP. For the other variables, see Table10A. Notes.




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transition countries from the adverse effects of the crisis. Economic liberaliza-

tion and small public sectors led to more rapid growth in normal times, but free

markets and economic integration in the global economy made transition coun-

tries more vulnerable to the global financial crisis when it hit. The financial crisisplayed 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 allformer 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 differ-

ent speeds (Murrell, 2003). Given the well-established link between economic

and political freedoms, one might also have optimistically expected that eco-

nomic liberalization would eventually lead to democracy in all transition coun-

tries. 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 andorange 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 eco-

nomic 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 Republics promising first steps, might well havefaltered, and they too would have authoritarian regimes with weak economic

freedoms today. We cannot rule out the possibility, however, that the succ

Democracy Ec Freedom Trans Econ Peev Kyklos2012

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