Public support for creating a market economy in Eastern Europe

Journal of Comparative Economics 32 (2004) 720–744 www.elsevier.com/locate/jce

Public support for creating a market economy in Eastern Europe Bernd Hayo Philipps-University Marburg, Department of Economics (FB 02), D-35032 Marburg, Germany ZEI, University of Bonn, Germany Received 11 September 2002; revised 22 July 2004

Hayo, Bernd—Public support for creating a market economy in Eastern Europe Employing two large databases, we analyze the determinants of public support for the creation of a market economy in Eastern Europe. From a macroeconomic perspective inflation, unemployment, privatization, and enterprise restructuring reduce this support; alternatively, democratization, the creation of working financial markets, and foreign aid per capita increase support for the market. Across countries, higher inequality undermines market support. From a microeconomic perspective, labor market status, both the objective and the subjective economic situations of a person, political orientation, and the socio-demographic background of the respondent affect support for the market economy. For example, unemployed, relatively poor, older, female, and less-educated respondents living in rural areas are less inclined to favor the creation of a market economy. Journal of Comparative Economics 32 (4) (2004) 720–744. Philipps-University Marburg, Department of Economics (FB 02), D-35032 Marburg, Germany; ZEI, University of Bonn, Germany.  2004 Association for Comparative Economic Studies. Published by Elsevier Inc. All rights reserved. JEL classification: P1; P2; O52 Keywords: Economic transition; Market economy; Eastern Europe; Public support

E-mail address: [email protected]. 0147-5967/$ – see front matter  2004 Association for Comparative Economic Studies. Published by Elsevier Inc. All rights reserved. doi:10.1016/j.jce.2004.07.003

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1. Introduction Public support for the creation of a market economy is key to a successful transformation program. Williamson (1994) identifies strong political support for the reformer as one of the three most important ingredients.1 Although not a sufficient condition, public support appears to increase the chance that reforms will be feasible and successful (Stokes, 1996). Assessments of the actual progress in the Eastern European economic transitions, e.g. EBRD (1999) or IMF (2000), do not provide much information on determinants of public support for a market economy. On the theoretical side, Rodrik (1996), Drazen (2000) and Roland (2002) survey the growing body of work on economic policy reform, in which public support for the reforms, either directly or indirectly, is crucial. However, most theoretical models simply assume that certain variables, especially unemployment and per capita income, are important determinants of public support for reforms, without providing the empirical evidence to support these assertions. Our analysis investigates the determinants of public attitudes towards creating a market economy by employing survey data collected in Eastern European countries, which are in the process of transforming their centrally planned economies into Western-style market economies. While no general theory of transition is available, Blanchard (1997) presents a partial equilibrium model of economic transformation. His model consists of a transition economy in which decision-makers have perfect foresight to capture the stylized fact of a U-shaped evolution of output and employment in most Eastern European economies. The author assumes that public support for economic reforms is also U-shaped. Blanchard provides survey evidence from Poland regarding the determinants of the perception of both the current and the expected economic situations of people and shows that unemployment and output do affect attitudes. However, if the democratic political process were to be endogenized, Blanchard (1996) demonstrates that the chosen reform path might not be achievable. Fidrmuc (2000) investigates public support for the market in Eastern Europe empirically, but indirectly. He uses election results from four countries to analyze political support by explaining voting shares for reform and non-reform parties using various regressors, e.g., unemployment, entrepreneurial activity, and demographic factors. Actual votes may indicate true revealed preferences rather than only the intentions reported by respondents in surveys. However, voting for a party cannot be attributed easily to only one policy issue. Therefore, it is not clear whether voters prefer a party because of its stance on economic reform or because of its position on maintaining order, improving democracy, or national defense. Warner (2001) investigates the relationship between the intensity of market reforms and electoral support for reform parties in Russian regions from 1990 to 1995. He finds that reform parties garnered more support in the 1995 parliamentary elections in those regions where greater progress was made in structural reforms. In principle, public attitudes towards creating a market economy can be measured directly from opinion polls. Early attempts by Shiller et al. (1991, 1992) to compare Eastern European attitudes with those of Western countries are interesting but limited to studying 1 The other two listed conditions for successful reforms are a visionary leadership and a coherent economic team.

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whether Eastern European opinions during times of transformation contain an attitudinal legacy from Communist times.2 Concentrating on the labor market and taking into account a time dimension, Blanchflower abd Freeman (1997) compare the market attitudes of respondents in Eastern and Western Europe using the large International Social Survey Programme (ISSP) database. In contrast to Shiller et al., these authors find evidence of an attitudinal legacy from the Communist times.3 In comparing the development in Poland and Russia, Shleifer (1997) incorporates possible differences in trust and participation in civic activities, which he computes using the World Values Survey. In his view, the emerging differences in social capital are not a key determinant of differences in economic performance. Eble and Koeva (2002) investigate attitudes towards market reforms in Russia after the crisis in 1998 using survey data.4 They find that individual attitudes towards reforms are affected by the personal experiences of the respondents during the transition process. In addition, groups that are distinguished by education and age appear to be more flexible in adjusting to new situations. Finally, these authors conclude that respondents from Russian regions in which a high percentage of workers have received no wage payments within the last month are not supportive of market reforms. Our paper investigates public support for creating a market economy empirically using two representative survey databases, namely the Central and Eastern Eurobarometers (CEEB) and the New Democracy Barometers (NDB). Both surveys ask about the respondent’s attitude towards the creation of the market but not about particular reform strategies that will lead to a market system. We employ static and dynamic panel data methods in the macroeconomic level analysis and cross-section regressions in the microeconomic level analysis. The paper is structured as follows. In Section 2, the database and econometric methodology are described. Theoretical reasons for an aggregate analysis of support for a market economy are summarized in Section 3 and the corresponding empirical results are shown in Section 4. Section 5 presents microeconomic level analyses using the NDB and CEEB data. The final section concludes with policy implications.

2. The databases The Central and Eastern Eurobarometers (CEEB) database, which is collected on behalf of the European Commission, is used for macroeconomic analysis because the number of countries and the collection of repeated cross-sections over time make it possible to construct a panel data set using average national values. In general, about 1000 people in each country were selected randomly for a personal interview in the autumn of the respective year. The first surveys in 1990 were undertaken only in Czechoslovakia, Hungary and Poland, while the most extensive survey from 1996 provides data on twenty countries.5 2 This idea is related to the importance of initial economic and political conditions to the success of the

transformation (de Melo et al., 2001). 3 Frentzel-Zagorska and Zagorski (1993) provide survey evidence from Poland on this issue. 4 Finifter and Mickiewicz (1992) document survey evidence from the former USSR. 5 The primary data are available from the Zentralarchiv für Empirische Sozialforschung (ZA) in Cologne (http://www.za.uni-koeln.de/index-e.htm). This survey project ended in 1997.

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Single CEEB surveys have been aggregated to cover the time period from 1990 to 1997 and include data on 21 countries.6 Hence, the aggregated data base contains responses from about 120,000 people. Using the CEEB data, Kim and Pirttilä (2003) find evidence that countries showing greater public support for market reforms also achieve higher growth rates eventually. To control for possible endogeneity, we use the general method of moment (GMM) estimation technique. The CEEB data have problems concerning the consistent and regular coverage of important questions across different surveys because many interesting questions are eliminated over time. In addition, only a few demographic variables are collected over time and some countries are also eliminated. The New Democracy Barometers (NDB) database, which was initiated by the Centre for Public Policy at Strathclyde University in Glasgow, is used for microeconomic analysis of a cross-section in 1995. Because it contains a rich set of individual-level questions, we can control explicitly for several potentially important factors. On the downside, the NDB covers only seven countries, namely the Czech Republic, the Slovak Republic, Slovenia, Hungary, Poland, Romania, and Bulgaria, and contains only one relevant round of surveys in 1995 for our question of interest. The NDB is based on personal interviews and designed to be a random sample of the population (Rose and Haerpfer, 1993).7 Although limited in terms of available variables, the CEEB database can also be used in microeconomic analysis to investigate the robustness of the results from the NBD. However, we must be confident that we are measuring similar things in the two databases. The CEEB database focuses on one issue, namely a person’s opinion about the creation of a market economy. The specific question is: Do you personally feel that the creation of a free market economy, that is one largely free from state control, is right or wrong for (our country’s) future? The answers to that question are coded into three categories, namely ‘wrong’ (−1), ‘don’t know’ (0), and ‘right’ (1), to form the dependent variable called SUPPORTCEEB. To get aggregate values, we compute the mean values of SUPPORTCEEB for every country at each point in time.8 In the case of NDB, we create a variable measuring market support that may be advantageous methodologically because it measures the concepts of interest directly. The notion of a market economy is not defined easily so that capturing it by asking one specific question is problematic. The NDB uses four variables related to core aspects of a market economy. The questions investigate whether people prefer differential or equal incomes, private or state property, high pay but job risk or a secure job, and many goods but high prices or price controls. Considering more than one indicator increases the 6 Observations from Albania, Armenia, Belarus, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Latvia, Lithuania, Macedonia, Moldova, Poland, Romania, Russia, Slovakia, Slovenia, Ukraine, Yugoslavia are included. 7 The primary data for the NDB are not accessible for researchers who are not members of the Citizens in Transition Network (CITNET). 8 Keeping the ‘don’t know’ responses is highly desirable for maintaining representativeness of the sample. However, forming a dichotomous dependent variable by dropping the ‘don’t know’ category yields similar results.

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chances that we are measuring actual attitudes towards the market in general and not just perceptions about a single aspect of the market economy. Taking into account these considerations, we condense the information from the NDB through factor analysis. As Appendix Table 1 in the reports, exactly one factor can be extracted and all of the factor loadings are larger than the usual threshold of 0.5. We interpret the factor extracted from the four questions as indicating public support for the market economy and denote it SUPPORTNDB. Moreover, this factor is valid not only at the aggregate level but also at the national level. The Spearman rank correlation coefficient between the averages of SUPPORTCEEB and SUPPORTNDB based on the ten countries covered in the NDB in 1995 is 0.72, which is significant at a 5% level. Hence, we find strong support that the two variables from different data sources measure a similar concept. Figure 1 plots public support for the market economy over time using averages of SUPPORTCEEB for the countries in the sample. These values can be interpreted as the share

Fig. 1. Public support for the market economy across countries: mean values for SUPPORTCEEB.

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Fig. 2. The aggregate evolution of support for the market economy.

of net supporters, i.e. supporters minus opponents in relation to all respondents, of the creation of a market economy.9 In the next section, the apparent differences across countries are investigated statistically, conditional on the influence of other explanatory variables. To generate information about the overall time trend for market support in Eastern Europe, two regressions are run to analyze market support first by year dummies only and then by year and country dummies. The resulting coefficients for the year dummies are plotted in Fig. 2; both series indicate that support was at a minimum in 1994. Although the coefficients obtained from the regression having only year dummies are consistent with the prediction of Blanchard (1997) that support for the market is U-shaped over time, the series based on the regression including year and country dummies is multi-peaked.10

3. Theoretical determinants of support for the market at the aggregate level The relevant variables for investigating public support at the aggregate level are listed in Table 1 with descriptive statistics and expected effects included. These variables are chosen based on the literature and divided into categories of indicators, namely, macroeconomic indicators, standard of living, fiscal policy, transition progress, external influences, political institutions, and political business cycles. Lipton and Sachs (1990) claim that fundamental economic reform involves three core elements, namely, macroeconomic stabilization, economic liberalization, and privatization of state enterprises. Williamson (1994) provides a similar list, denoting it as the Washington Consensus. In addition, Drazen (2000) stresses the importance of political institutions and processes in economic policymaking to justify the inclusion of political institution and indicators of the political business cycle. 9 Standard deviations to measure dispersion are also computed to investigate the consensus of opinion within society. The average of SUPPORTCEEB and its standard deviation are negatively correlated with a coefficient of −0.60 that is significant at a 1% level. Hence, the lower is the degree of support for market reforms, the larger is the disagreement in society on this issue. 10 Because not all Eastern European countries started economic reforms at the same time, it may be more meaningful to include a proxy for transformation or stabilization time. Therefore, we constructed transformation time trends that count years since the start of economic stabilization programs (Fischer et al., 1998). However, a transformation trend variable and its square are both less significant than the year dummies (Hayo, 1999b).

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Table 1 Aggregate variables: sources, descriptive statistics, and priors Variable name

Definition

Dependent variable SUPPORTCEEB Country average of individual level attitudes towards creating a market economy Macroeconomic indicators DGDP GDP growth, in % UNEMP Unemployment rate, in % INFLAT Inflation rate, in % p.a. FXRATE Change in log of exchange rate against SDR, in % Standard of living indicators GDPCAP GDP per capita, in constant US dollars (base: 1995) RADIOS Number of radios in the country (per 1000 people) LIFEEXP Life expectancy GINI1 Gini coefficient GINI2 Gini coefficient (adding WDI Gini coefficients of countries not in GINI1) Fiscal policy indicators GOVGDP Ratio of government expenditure to GDP, in % GOVDEF Ratio of government surplus to GDP, in % (deficit = negative value) Transition indicators ENTERPRISE Average of large-scale privatization, small scale privatization, and enterprise restructuring MARKETS Average of price liberalization, trade and foreign exchange system, and competition policy FINANCE Average of banking reform and interest rate liberalization, and securities markets and non-bank financial institutions External indicators OPENNESS Ratio of trade in goods and services to GDP, in % AIDGNP Foreign aid in relation to GNI, in % AIDCAP Foreign aid per capita, in US dollars FDICAP Net foreign direct investment per capita, in US dollars

Source

Mean

Std. dev.

Expected sign

CEEB

0.12

0.28

EBRD EBRD EBRD IMF

−0.22 10.14 260.20 192.65

7.69 5.18 780.14 676.00

+ − ? ?

WDI

2830.30

2157.90

+

WDI

473.75

178.68

+

WDI Milanovic Milanovic, WDI

70.08 34.36 32.35

2.47 11.07 8.26

+ − −

EBRD

41.67

8.59

?

EBRD

−4.95

6.95

?

EBRD

2.68

0.76

+

EBRD

2.84

0.47

+

EBRD

2.16

0.63

+

WDI

92.39

34.33

−

WDI

2.04

3.59

+

WDI

26.30

20.87

+

571.00

833.08

?

EBRD

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Table 1 (continued) Variable name IMFSUPPORT

Definition

Dummy variable: IMF program running at the time of the survey Political institutions indicators EXREC Executive recruitment EXCONST Executive constraints POLCOMP Political competition POLCONV Number of independent branches of government with veto power over policy change including the judiciary and sub-federal units Political business cycle indicators ELECTYEAR Dummy variable, taking the value 1 if an election occurs in that particular year

Source

Mean

Std. dev.

Expected sign

IMF

0.38

0.49

+

Polity Polity Polity Henisz

7.45 5.95 8.04 0.54

1.25 1.48 1.88 0.29

+ + + −

Fidrmuc

0.39

0.49

+

Notes. Only 78 observations are used to compute the descriptive statistics that correspond to those employed in the analysis in Table 2. Sources. CEEB: Central and Eastern Eurobarometers survey database. EBRD: Transition Report. IMF: International Financial Statistics. IMF program constructed using information from http://www.imf.org/ external/country/. WDI: World Bank Development Indicators CD-Rom 2002. Milanovic: Branco Milanovic’s estimates http://www.worldbank.org/research/transition/house.htm). Polity: Polity IV database (http://www.cidcm. umd.edu/inscr/polity/). Henisz: Henisz (2000). Fidrmuc: We extend special thanks to Jan Fidrmuc for providing these data.

For macroeconomic indicators, we take inflation, exchange rates, unemployment, and GDP growth. Typically, the IMF proposes stabilization programs to reduce high rates of inflation. Moreover, in survey data, people often express serious concern about inflation (Di Tella et al., 2001; Fischer and Huizinga, 1982; Hayo, 1998a, and Rose, 1998). However, neither theoretical nor empirical evidence of negative economic effects of moderate inflation is compelling, as Driffil et al. (1990) and Bruno and Easterly (1998) attest. Nonetheless, inflation rates in excess of 1000 percent per year have been observed in some of the transition countries, e.g., Armenia, Belarus, and Kazakhstan. Thus, we conjecture that inflation may influence public support for the creation of a market economy in a nonlinear fashion. For transition countries, Fischer et al. (1996a, 1996b) argue that eliminating high inflation is a requirement for economic growth. Yavlinsky and Braguinsky (1994) think that alternative policies, e.g., de-monopolization, should be addressed before monetary policy is tightened. Finally, Mondino et al. (1996) present a model of an inflation cycle, in which inflation goes down rapidly after the adoption of a stabilization program but increases again when the reform is abandoned. In their model, the inflation rate drives public support for reforms and, as soon as the inflation rate is reduced significantly, support for the program collapses. Thus, evidence of the actual effects of inflation on public opinion towards economic reforms may contribute to an assessment of these conflicting hypotheses. For robustness, we consider the exchange rate as another indicator of inflationary conditions.

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Hence, we designate an ambiguous expected sign for inflation and the exchange rate in Table 1. Unemployment is included to capture the labor market situation, following the theoretical models of Blanchard (1997), Fidrmuc (1999), and Rodrik (1995). However, measuring unemployment in transition countries may be unreliable (UN, 1997, p. 114f).11 Nonetheless, we expect higher unemployment to lead to less support for reforms so we report a negative expected sign for this variable in Table 1. In addition, we consider GDP growth because it contains information about the dynamic effects of income evolution in the respective economies. Typically, living standard is proxied by income per capita, which is an important component in many theoretical models of public support for reforms. Alternative indicators to national accounts data for measuring the standard of living, namely life expectancy and the number of radios in a country, are included to assess the robustness of our findings. The growth of GDP and the three standard of living indicators are expected to have a positive effect on support for reforms. In addition Drazen (2000) argues that the distributional consequences of economic reforms may lead to strong opposition to the creation of the market. Thus, we include the Gini index as a measure of income inequality and expect the sign of the coefficient to be negative. Although IMF programs emphasize a reduction in both the share of government expenditures in GDP and budget deficits, East European countries may find it beneficial to incur some fiscal debt during the transition period. Fernandez and Rodrik (1991) show that the existence of ex ante uncertainty about winners and losers from the reforms may prevent the implementation of efficiency-enhancing reforms, even though people would have supported the reforms ex post. Hence, if people can be assured that they will benefit from the reforms, even if they turn out to be losers according to the previous distribution of income, the likelihood of public support for the reform will be higher. Alesina and Drazen (1991) make a similar argument based on a war of attrition. Since fiscal budgets are dominated by social spending, a large share of government expenditures with a resulting high budget deficit mitigates the adverse distributional consequences of the transformation. Due to countervailing tendencies, we report ambiguous signs for the fiscal policy indicators in Table 1. The EBRD computes indices to reflect the extent of small-scale and large-scale privatization, enterprise restructuring, and price liberalization. In addition, progress in liberalizing trade and foreign exchange, the development of competition policy, and the reform of banks and other financial institutions are measured. Stiglitz (1999) argues that privatization has not been successful in most East European countries because the problems encountered in this process have a negative impact on public support for market reforms. Nevertheless, we expect improvements measured by the three aggregate EBRD transition indicators to have a positive impact on support for reforms as Table 1 records. Regarding external influences, Krueger (1993) shows that certain trade policies may have asymmetric effects on different groups within an economy and, thus, affect the balance of political power. Furthermore, some groups may link economic problems to foreign 11 In an earlier working paper, we used employment rather than unemployment and the corresponding esti-

mation results were not significant. In addition, several problems arise when computing real GDP per capita but using an index instead of an actual value did not yield very different results (Hayo, 1999b).

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capital or international trade, as La Ferrara (1996) asserts. Although foreign direct investment (FDI) can be a catalyst in modernizing the transition economies, a high share of FDI may indicate that foreigners have an unwelcome position of power. For these reasons, we consider the degree of openness of the economy to have a negative impact and FDI to have an ambiguous effect on public attitude to reform. On the other hand, foreign economic aid may facilitate the creation of a market if it comes from market economies. Hence, we expect foreign aid to have a positive impact on support for reforms as Table 1 reports. The IMF plays a prominent role in Eastern Europe not only by providing guidance on macroeconomic policies and structural reforms but also by providing extensive credit programs. Since its intervention is not always viewed as beneficial as Stiglitz (2003) argues, whether or not the existence of such an active credit program affects public support for market reforms in a country is an open question but we expect these programs to have a positive effect on balance. With respect to political institutions, empirical evidence indicates that the introduction of economic reforms is influenced by initial conditions and by changes in the political system (de Melo et al., 2001; Falcetti et al., 2002; EBRD, 1999). In addition, Hayo (2001) claims that economic developments affect public perceptions of the progress in political reforms towards democracy. To capture the impact of political institutions, we consider the effects of the impartiality of executive recruitment practices, the constraints facing the executive, and the degree of political competition. The latter variable characterizes constraints to political participation and the expression of alternative preferences for policy and leadership. These three variables are taken from the Polity IV database, which contains information on regime and authority characteristics for all independent states and covers years from 1800 to 2002. Our working hypothesis is that, if these measures are close to those in Western-style democratic political systems, the probability of establishing a market economy will be higher so that we record positive expected signs for their coefficients in Table 1. Data are also available in Henisz (2000) on the degree of veto power within the political system, which affects the ability of the political system to implement market reforms. We expect this variable to have a negative influence on public support for reforms. Finally, we consider the effect of a political business cycle by including a dummy variable if an election occurs in the current year. We expect elections to have a positive impact on public support for market reforms because politicians will try to improve the performance of the economy so as to increase their chances of re-election.

4. The estimation results at the aggregate level Initially, we investigate net support for market reforms at an aggregate level using an unbalanced panel across countries and years. To avoid problems caused by missing data, the sample starts in 1991 and excludes Moldova and Yugoslavia. In the empirical analysis, we take into account all potentially important variables in a single model because the inclusion of variables one by one, or in groups, may lead to spurious results. However, having

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a large model containing many insignificant variables is not desirable.12 Under these circumstances, Hendry (1993) advocates a modeling strategy moving from general to specific to ensure that the inferences drawn are statistically valid throughout the reduction process. Since statistical inference may be path-dependent, the final parsimonious model might not be an encompassing one. Based on the examination of the vices and virtues of data mining by Hoover and Perez (1999), Hendry and Krolzig (1999) develop a model reduction algorithm, denoted GETS, that is surprisingly powerful in recovering the underlying data generating process. Moreover, GETS ensures that a favorable diagnostic test result for the general model is preserved during the reduction process. Applying this empirical approach has its drawbacks. First, the number of variables that can be analyzed consistently is limited by the available degrees of freedom. As is often done in similar studies, analyzing blocks of variables in separate models allows us to consider many more variables. Second, the outcome of the reduction process depends on the general model. Including some variables but not others may affect significantly the resulting parsimonious model. Finally, generating a data set that contains no missing values for all the relevant variables reduces our sample size from 101 to 78. The statistical validity of the general model is crucial to the GETS algorithm.13 We encounter some problems with the normality assumption caused by two outliers; these are neutralized by including dummy variables for the Czech Republic in 1996 and Romania in 1991. Model 1 in Table 2 reports the outcome of the reduction process using all the explanatory variables listed in Table 1, except for the Gini coefficients, and including dummies for years, countries, and outliers. The F -test for testing down in the next-to-last row indicates that the model presented is an admissible reduction of the general model. With regard to the diagnostic tests, we cannot reject normality or homoscedasticity; inaddition, we find no evidence of autocorrelation or of misspecification using a first-order RESET test (Ramsey, 1969). Since the White (1980) test may not pick up heteroscedasticity within the panel structure of the data, we also report heteroscedastic-consistent standard errors (HCSE) in an added column. Regarding the deterministic components, none of the yearly dummies survives the testing-down process. Compared to the Czech Republic and conditional on the influence of the other variables in Model 1, market support is significantly lower in the Ukraine and Russia, similar in Armenia, Belarus, Georgia, Kazakhstan and Slovenia, and higher in the rest of the countries listed in Table 2. Of the macroeconomic variables, only inflation and unemployment survive reduction. An increase in the inflation rate of 100 percent per annum decreases the share of net support for the market economy by one percentage point, which is equivalent to saying that 10 respondents out of 1000 who were undecided before the increase in inflation would not support the creation of a market economy after the change. To assess the economic significance of the analyzed variables in contrast to their statistical significance, we evaluate their impact on public support at their means across countries given in Table 1. This table also contains the standard deviations of the 12 Hayo (1998b) presents some methodological remarks regarding the advantages of simple models. 13 Constructing average country values based on ordinal individual observations is problematic. However, Hayo

(1999b) shows that many of these results hold if an ordered logit model that adjusts the standard errors of the macroeconomic variables is estimated at the individual level.

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respective variables to indicate how representative the mean is for a particular country. Evaluating the effect of the inflation rate at its mean, which is about 260 percent, shows a reduction in the share of net support by 2.6 percentage points. This effect has a noticeable impact on public support in countries with high inflation rates, e.g., Armenia, Belarus, and Kazakhstan, while it has little relevance for most other countries. Hayo (1999b) does not find a non-linear relationship between inflation and support for reforms when he includes inflation in logs or adds squared values. Hence, we conclude that people react to inflation in these countries by reducing their support for reforms in an approximately linear way, especially in high inflation countries. Table 2 Aggregate level estimation: testing-down procedure Model:

1

Estimator:

OLS

Variables

Coefficients

SE

HCSE

Coefficients

ASE

−0.0001*** −0.016*** 0.002** 0.104** −0.171*** 0.037***

0.00002 0.004 0.001 0.043 0.037 0.009

0.00002 0.004 0.001 0.052 0.050 0.012

−0.057 −0.0001*** −0.007 0.002** 0.128** −0.158** 0.039**

0.177 0.00002 0.006 0.001 0.063 0.061 0.018

0.549*** −0.746***

0.112 0.116

0.045 0.044

0.738*** 0.304*** 0.403*** 0.225*** 0.178*** 0.281*** 0.449*** 0.506*** −0.319*** 0.218*** −0.392***

0.083 0.056 0.062 0.054 0.066 0.060 0.056 0.053 0.070 0.068 0.073

0.102 0.076 0.070 0.048 0.058 0.065 0.057 0.042 0.040 0.051 0.068

Substantial variables SUPPORTCEEBt-1 INFLAT UNEMP AIDCAP FINANCE Enterprise Polcomp Outliers Czech Republic, 1996 Romania, 1991 Country dummies Albania Bulgaria Estonia Hungary Latvia Lithuania Poland Romania Russia Slovak Republic Ukraine No. of obs. SE of regression Pseudo-R 2 F -test, all variables F -test, substantial Variables Autocorrelation Heteroscedast. Normality

2 Panel GMM

78 0.104 0.90 F (19, 59) = 32.2*** F (6, 59) = 15.3***

45 0.175 0.65 χ 2 (7) = 82.3*** χ 2 (6) = 75.6***

N (0, 1) = −1.30 F (25, 33) = 0.96 χ 2 (2) = 0.81

N (0, 1) = 0.68

(continued on next page)

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Table 2 (continued) Model:

1

2

Estimator:

OLS

Panel GMM

Variables

Coefficients

RESET Testing down Sargan test

F (1, 58) = 0.03 F (28, 31) = 0.89

SE

HCSE

Coefficients

ASE

χ 2 (91) = 38.5

Notes. 1. The sample period is 1991 to 1997. 2. Moldova and Yugoslavia are excluded due to missing observations. 3. Model 1 results from a GETS testing-down process based on a model that contains a full set of country dummies (base: Czech Republic) and year dummies (base: 1991), a constant, dummies for Czech Republic in 1996 and Romania in 1991, and the variables DGDP, UNEMP, INFLATION, FXRate, GDPCAP, RADIOS, LIFEEXPECT, GOVGDP, GOVDEF, ENTERPRISES, MARKETS, FINANCE, OPENNESS, AIDGDP, AIDCAP, FDICAP, IMFSUPPORT, EXREC, EXCONST, POLCOMP, POLCONV, and ELECTIONYEAR. 4. Autocorrelation is a panel data test for autocorrelated residuals of order two; heteroscedasticity is the White (1980) test using squares of the regressors; heteroscedasticity-consistent standard errors (HCSE) are based on White (1980). Normality is the Jarque and Bera (1987) test with a small-sample correction and RESET is a misspecification test developed by Ramsey (1969). The Sargan test relates to the orthogonality condition between instruments and error term. 5. The Pseudo-R 2 statistics are based on the correlation between the original series and the fitted series. 6. Model 2 uses the GMM Arellano–Bond (Arellano and Bond, 1991) one-step estimator in first differences. The robust standard errors (ASE) are computed according to Arellano (1987). The level instruments are lags 2 to 5 of the variables UNEMP, INFLATION, ENTERPRISES, FINANCE, AIDCAP, and POLCOMP. ** Significance at the 5% level. *** Idem., 1%.

We find that increasing the unemployment rate by one percent reduces the share of net support for the market by 1.6 percentage points. However, this estimate is not very robust as it depends upon the particular specification of the model (Hayo, 1999b). Evaluating the effect of the unemployment variable at its mean, which is about 10%, unemployment reduces the share of net support by about 16 percentage points. Thus, unemployment has the expected negative effect and its quantitative effect is moderate. Nonetheless, the labor market experiences of Eastern Europeans can be considered as only one determinant of public support for the reforms. In a similar exercise, Valev (2004) finds that the power of unemployment in explaining voting for reform parties in Bulgaria is limited. None of the indicators for the standard of living or for the fiscal policy stance survives the testing-down procedure. However, two EBRD transition progress indicators are significant.14 First, improvements in financial deregulation and the establishment of functioning financial markets increase support for reforms. The economic impact of this variable, measured at its sample mean, on the net share of support is 23 percentage points. Second, the variable capturing privatization and enterprise restructuring is negative and significant in most East European countries, which is consistent with the view that privatization has not been a major success. Moreover, the quantitative effect at its mean on the net share of support for reforms at 46 percentage points is twice as large as that of the financial progress indicator. Using this 14 Krueger and Ciolko (1998) argue that the liberalization indices overemphasize the role of policy because they are partially endogenous with regard to the outcomes.

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method of quantification, privatization also has a much larger negative impact on public support for reforms than does unemployment. Regarding the external influences, foreign aid per capita has a significantly positive effect on public support for the market. At its mean value of 26.3, the economic impact of this variable on the net share of market support is small at 5 percentage points. To keep net market support constant when unemployment increases by one percentage point, annual foreign aid would have to rise by about 300 dollars per capita. Such an increase is more than ten times the average annual foreign aid actually paid over the sample period. Of the political institution indicators, only political competition has a significant impact on public support for market reforms. At its sample mean of 8.04, political competition increases the share of net support by 30 percentage points, which is a sizeable effect. Since the upper limit of this indicator is 10, further progress in democratization will raise the share of public support for the market by a maximum of 7 percentage points only. Nonetheless, increasing the degree of democratization affects support for the market economy positively. The transition in Eastern Europe is viewed by the populace as comprising both the introduction of a market economy and the creation of a democratic political system (Hayo, 2001). Hence, the Asian strategy of separating economic and political reform is not relevant for Eastern Europe. Finally, we find no evidence of a significant influence of the political business cycle on public support for the market economy. To check the robustness of our findings, we investigate reverse causality, i.e. the possibility that public support affects the explanatory variables. The graphs in Fig. 1 indicate some persistence in the support variables, which necessitates the inclusion of a lagged dependent variable as a regressor. Thus, we re-estimate Model 1 using a general method of moments estimator (GMM) with a lagged dependent variable (Arellano and Bond, 1991). In Model 2 of Table 2, the lagged dependent variable is not significant; in addition, the signs, and even the sizes, of most coefficients with the exception of unemployment are almost unchanged. Since endogeneity does not appear to bias the coefficients in the ordinary least squares regression (OLS), we conclude that the results from the static panel data model are robust. Given that we would expect lags in the impact of public support for economic reforms on actual performance, this result is not surprising. Finally, we consider the effect of inequality as measured by the Gini coefficient and report our results in Table 3. Due to missing values, the relevant sample is small and the statistical tests lose much of their power. However, all models in Table 3 pass the diagnostic tests listed in Table 2. In Model 3, we restrict the analysis to a bivariate framework using the Gini coefficients computed by Milanovic, which are comparable across countries. We find negative and significant effects of inequality on public support for reforms at a 10% level of significance. To analyze the robustness of this result, we extend the inequality series by adding the Gini coefficients as computed by the World Bank, although full comparability across countries is no longer ensured. We estimate the impact of inequality on market support by including year dummies to control for trend or cycle effects in Model 4. The coefficient on the Gini variable is smaller in magnitude than that in Model 3 but it is now significant at the 5% level. Then, we include country but not year dummies as controls in a model with this Gini coefficient in Model 5. The addition of country dummies causes the Gini coefficient to lose its statistical significance. Hence, the Gini coefficient explains

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Table 3 Aggregate level estimation: inequality Model:

3

4

Estimator:

OLS

OLS

Variables

Coeff.

SE

HCSE

GINI1 GINI2 CONSTANT Year dummies Country dummies No. of obs. R2 F -test

−0.02*

0.008

0.005

0.71**

0.28 no no 11 0.315 F (1, 9) = 4.1*

0.26

Coeff. −0.012** 0.60***

5 OLS SE

0.006 0.18 yes no 37 0.302 F (7, 29) = 1.8

HCSE

Coeff.

0.006 0.19

0.004 0.13

SE

HCSE

0.011 0.009 0.27 0.23 no yes 37 0.750 F (15, 21) = 4.2***

Notes. 1. The sample period is 1991 to 1997. 2. The estimated equations pass all of the diagnostic tests listed in Table 2 for Model 1. 3. GINI1 is the inequality measure computed by Milanovic, while GINI2 combines GINI1 with data from the WDI. 4. The data contain observations that are not included in Model 1 of Table 2 to increase the degrees of freedom. * Significance at the 10% level. ** Idem., 5%. *** Idem., 1%.

differences in public support for market reforms across countries to some extent but it has no explanatory power across time within countries. To summarize the results from the aggregate analysis, we find that lower values of the inflation rate, the rate of unemployment, and the degree of privatization increase public support for the creation of a market economy. Public support also rises as a consequence of higher values of foreign aid per capita, the degree of restructuring of the financial system, and democratization. In the theoretical literature on economic reforms, the unemployment rate is assumed to be of particular importance. We find noticeable economic effects of this variable but, among this group of statistically significant determinants of market support, the EBRD indicator for privatization progress has the biggest influence.

5. Determinants of support for the market at the individual level In this section, we switch focus from the macroeconomic perspective to the microeconomic view by using SUPPORTNDB as the dependent variable in regressions investigating people’s individual opinions of market creation. Because the sample is relatively large, we use a significance level of 1%, which makes the tests very sensitive to a violation of the null hypothesis (Leamer, 1983). By extracting the factor that describes support for the market economy, we create a variable with a pseudo-cardinal scale. Hence, the regression analysis is relatively straightforward and we can use OLS. The first two columns of Table 4 report coefficient estimates for a regression that includes all the variables, while the last two columns contain only those variables that remain after a consistent testing-down process. The White (1980) test for heteroscedasticity is significant so that we compute robust standard errors to ensure valid inference. The large sample size makes the use of these standard

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Table 4 Public support for the market economy at the individual level Estimator: General economic situation Economic system evaluation Socialist system good Current system good Privatization speed Right speed Too slow Personal employment situation Type of employer State enterprise Privatized enterprise Private enterprise Co-operative farmer Independent farmer Type of employment Part-time employment Apprentice Unemployed Pensioner Allowance Housewife, student Most important personal economy House repairs Paid for favors Help of friends Currency Second job Paying tips First job Pensions, benefits Job benefits Objective economic situation Income Lower-middle quartile Upper-middle quartile Highest quartile Financial situation Got by Spent savings Borrowed money Spent & borrowed Living conditions Never without food Never without heating Never without needed clothes

OLS

OLS

Coefficients

HCSE

Coefficients

HCSE

−0.293*** 0.093***

0.023 0.022

-0.294*** 0.093***

0.022 0.021

0.145*** 0.215***

0.034 0.027

0.136*** 0.227***

0.033 0.027

−0.078*** 0.046 0.067 −0.036 0.106

0.030 0.044 0.041 0.068 0.128

−0.086***

0.024

−0.025 0.135 −0.106** −0.098** −0.042 0.010

0.049 0.133 0.052 0.049 0.059 0.050

−0.147*** −0.133***

0.044 0.037

−0.021 −0.284** −0.058 0.500*** 0.159 −0.124 0.028 −0.060 −0.064

0.054 0.135 0.072 0.152 0.065 0.079 0.031 0.036 0.154

0.516*** 0.158***

0.148 0.060

−0.001 0.118*** 0.192***

0.028 0.031 0.033

0.129*** 0.210***

0.025 0.027

−0.104*** −0.064 −0.162*** −0.088

0.036 0.042 0.047 0.056

−0.075***

0.022

-0.132***

0.034

0.062** 0.031 0.071***

0.025 0.025 0.024

0.077***

0.024

0.079***

0.024

(continued on next page)

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Table 4 (continued) Estimator: Subjective economic situation Personal economics situation Was better 5 years ago: Yes Will be better in 5 years time: Yes Economic situation satisfactory: Yes Regular job income sufficient: Yes Political orientation Type of democrats Anxious democrat Dejected authoritarian Hopeful authoritarian Socio-demographic variables Age Age Age squared Gender effect Female Family size Number of children Education Vocational training Secondary School University Community size 5001–20000 inhabitants 20001–100000 inhabitants > 100000 inhabitants Church attendance Seldom Several times a year Once a month Every week Religion Protestant Orthodox Muslim Other Nonbeliever No answer Constant Valid cases F -test Adjusted R 2 Maximum Cook’s distance Heteroscedasticity test

OLS

OLS

Coefficients

HCSE

Coefficients

HCSE

−0.070*** 0.096*** 0.094*** 0.086***

0.022 0.020 0.025 0.030

−0.078*** 0.103*** 0.108*** 0.067**

0.021 0.020 0.024 0.027

−0.059** −0.150*** −0.255***

0.030 0.033 0.029

−0.130*** −0.232***

0.032 0.028

−0.012*** 0.00003

0.004 0.00004

−0.009***

0.001

−0.121***

0.020

−0.117***

0.020

0.011

0.013

0.121*** 0.247*** 0.433***

0.030 0.029 0.036

0.123*** 0.251*** 0.441***

0.029 0.028 0.035

0.012 0.092*** 0.164***

0.030 0.027 0.030

0.081*** 0.157***

0.023 0.026

0.060 0.084** 0.117*** 0.081**

0.033 0.035 0.043 0.040

0.053** 0.085***

0.024 0.033

−0.027 −0.010 −0.087 0.027 0.010 −0.029 0.096

0.048 0.040 0.080 0.058 0.040 0.063 0.117

0.114

0.067

8321 F (69, 8251) = 57*** 0.27 0.005 F (71, 8179) = 1.93***

8321 F (34, 8286) = 111*** 0.27 0.008 F (35, 8250) = 1.92*** (continued on next page)

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Table 4 (continued) Estimator:

OLS Coefficients

RESET Test (fourth order) Test for excluding variables

F (3, 8248) = 3.79**

OLS HCSE

Coefficients

HCSE

F (3, 8283) = 3.52**

F (35, 8251) = 1.62**

Notes. 1. The sample period is 1995. 2. Country dummies for Czech Republic, Bulgaria, Slovakia, Hungary, Poland, Romania, Slovenia, Belarus, and Ukraine are included in the regressions. 3. The reference categories are: Privatization speed (too fast), Type of employer (public agency), Type of employment (full-time employment), Most important personal economy (growing food), Income quartiles (lowest quartile), Financial situation (saved money), Type of democrats (confident democrat), Education (primary school), Community size (< 5000 inhabitants), Church attendance (never goes to church), and Religion (Catholic). ** Significance at the 5% level, using White’s heteroscedasticity-consistent standard errors (HCSE). *** Idem., 1%.

errors less problematic. A RESET test for misspecification of order four is not significant at a 1% level; hence, we conclude that the model is an adequate description of the data. The maximum value of Cook’s distance is very small, indicating that leaving out even the most influential observation will not alter the estimated coefficients substantially. An analysis of variance, which is not reported, shows high collinearity only for age and age squared. The explanatory variables are grouped according to categories, namely, the respondent’s evaluation of the general economy, indicators of the person’s employment situation, objective indicators of the person’s economic situation, subjective indicators of the economic situation based on the respondent’s characterization, the political orientation of the respondents, and socio-demographic variables. In our interpretation of the results, we focus on the variables that remain after the testing-down process. Starting with the overall economic situation, we find that people who are in favor of the socialist system do not support a market economy. Although this may seem obvious, the variable that characterizes the system evaluation did not load on the same factor as the ones that were combined into the dependent variable SUPPORTNDB. Similarly, people who are in favor of the current system also support the market but the magnitude of this effect is not as large as the previous one. Hence, the current system in 1995 is not seen, and correctly so, as a full-fledged market economy by the respondents. Respondents who believe that the speed of privatization is adequate are more in favor of the market economy than those who think it is too fast; however, those who consider the speed to be too slow are even more supportive of market reforms.15 Regarding the respondent’s employment situation, we find that those working for a state enterprise are least in favor of reforms because they are most likely to lose in a market economy. Analyzing the type of employment reveals that unemployed people are skeptical about market reforms, which is consistent with our findings at the aggregate level. In transition countries, pensions are not adjusted fully for inflation. Fidrmuc (2000) expresses surprise that he finds no straightforward evidence that a high share of pensioners vote against reform parties. In our data set, pensioners have significantly more critical attitudes toward the market economy than do full time employees. This result may explain partially 15 Hayo (1997) provides a more detailed analysis of attitudes toward privatization in Eastern Europe using CEEB data.

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the significant effect of the inflation rate in the macroeconomic analysis. Working in the regular job market is only one way to make a living, especially during a period of transition in which people have other sources of income. Those respondents who can get a second job or who obtain additional income by dealing with currencies tend to support the market reforms. Both of these activities were not permitted legally under the Communist rule so that they may be considered to be black market gains. Investigating the objective economic situation of the respondents, we find that those in the upper-middle and highest quartiles are more in favor of the market economy compared with the relatively poorer respondents. Apparently, this group has taken advantage of the new economic opportunities. In addition, relatively rich people are not exposed to the economic hardship resulting from greater income disparity that evolved in the transition years, as Cornelius and Weder (1996) and Milanovic (1999) discuss. Compared to those who are able to save some money, other groups are more negative about the market economy; the least support comes from those who have to borrow money to survive. The indicators for living conditions show that those not lacking food and clothes support the market more than the omitted group who face shortages of essentials. Although we do not find evidence of the impact of income and wealth in public opinion situation in the macroeconomiclevel analysis, we do find robust effects at the microeconomic level. This difference may be due to problems with official statistics in providing reliable information about living conditions, at least during the early stages of transformation (Hayo and Seifert, 2003). The subjective economic situation of the respondent also plays a role in determining attitudes towards the market economy. A person who felt better off in the past is less likely to favor market reforms, while a person who expects to be better off in the future will be more supportive of reforms. If today’s economic situation is considered satisfactory, the respondent indicates support. Finally, if the income from one’s regular job is considered sufficient, market support also increases. The political orientation of respondents is analyzed using a typology of democrats derived by Rose et al. (1998). We find that respondents with less democratic attitudes are less likely to support a market economy. A person who is hopeful that an authoritarian regime can run the economy successfully is less in favor of reforms than a person who considers an authoritarian regime to be only the better of two bad alternatives. This result is consistent with the empirical literature on economic and political transition in Eastern Europe that show people who support democracy will also support the market and vice versa, as Rose et al. (1998) and Hayo (2001) demonstrate. This result may also help to explain the significance of a political variable, i.e., the degree of political competition, in the aggregate analysis. Finally, we find that some sociodemographic variables also explain attitudes towards the market. The age of a person is an important consideration in the literature on modernization; we find a negative sign for this variable indicating that older persons are less in favor of reforms in accord with the views of Apter (1965) and Huntington (1968). In addition, women are less supportive of market reforms than men, which is consistent with results for Western Europe indicating skepticism about economic reforms among women (Gabriel, 1992; Hayo, 1999a). A possible explanation for this skepticism is the labor market barriers created for women as a result of reduced spending on child care opportunities and a change in equal employment practices. Furthermore, since women are less involved in the political

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and economic decision-making process, they may think that they cannot shape the changes in their countries. Experimental studies show that women tend to be more risk averse than men (Basow, 1986 and Sorrentino et al., 1992). Thus, women may be more reluctant to support major political or economic reforms, the outcome of which is uncertain. With regard to education, we find that people having more advanced degrees support market reforms, most likely because they can expect higher future returns from their education than would have been the case in a centrally planned economic system. Empirical evidence, e.g. Brainerd’s (1998) for Russia, Vecernik’s (1995) for the Czech Republic, Orazem and Vodopivec’s (1995) for Slovenia, and Rutkowski’s (1996) for Poland, indicates that persons with higher education fare relatively better under the new market system.16 Regarding the size of the community in which the respondent lives, we find that people who live in larger communities are more likely to support market reforms perhaps because more market opportunities are available in larger cities. Church attendance has a significant influence on public opinion; people who go to church moderately often but regularly tend to favor the market. Many political reform movements during the Communist era in Eastern Europe were linked closely to the church, especially in Poland; hence, people in these congregations are likely to view the market positively. In summary, we compare the microeconomic results derived from the NDB with those from the CEEB database. Table 5 reports the results of an ordered logit analysis with public support for market reforms measured by SUPPORTCEEB as the dependent variable. Differences between the significance of the coefficients for income and education and the ones from Table 4 are found for the second categories of income quartiles and education only. Regarding age, the CEEB data show a U-shaped effect compared with the linear relationship found using NDB data. However, the minimum effect of age on public support of reforms calculated from Table 5 is 66 years, while the age effect becomes positive at the irrelevant age of 132. Thus, non-linearity is not really relevant for realistic age spans. Overall, the microeconomic results are similar across the two data sets, which lends credibility to their interpretation.

6. Summary and conclusion In this paper, we investigate public support for the creation of a market economy using two large survey data sets. The questions in the surveys are directed towards the outcome of the reform process, i.e., a market economy, rather than the actual reform process itself. However, stronger support for the outcome makes the implementation of reform strategies easier for policy makers. If a fast-track approach produces high inflation, falling per capita income, and higher unemployment, combined with expectations of a medium-run recovery based on a fully re-structured economy, public support for market-oriented reforms may be dissipated before the process reaches a critical point (Bresser Pereira et al., 1993, and Dewatripont and Roland, 1992a, 1992b). Alternatively, if people do not attach much weight 16 Moreover, Ham et al. (1998) attribute the superior labor market performance of the Czech Republic as

compared to the Slovak Republic to the absorption of low-skilled workers, indicating that education is a good insurance against unemployment.

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Table 5 Explaining support for the market economy using SUPPORTCEEB (ordered logit) Variables Income Lowest income quartile Lower-middle quartile Upper-middle quartile Highest income quartile Education Primary school Vocational training Secondary school University Age Age in years Age in years squared Gender Female Valid cases Log likelihood χ 2 -test Pseudo R 2

Coefficients

Std. err.

Reference group 0.1266*** 0.2404*** 0.4979***

0.0178 0.0189 0.0197

Reference group 0.0266 0.3357*** 0.6712***

0.0208 0.0195 0.0245

−0.0409*** 0.00031***

0.0020 0.00002

−0.1969***

0.0131

93723 −88940.3 χ 2 (36) = 13074*** 0.069

Notes. 1. The estimates for country dummies, time dummies, and constant terms are omitted from the table. 2. The reference categories are: Income (lowest quartile) and Education (primary school). *** Significance at the 1% level.

to macroeconomic indicators when they choose to support market reforms, a rapid transition would be preferable. Blanchard (1997) predicts that the path of support for reforms will be U-shaped because, if one endogenizes political decisions, reforms may be delayed considerably. However, we find little evidence to support this conjecture. Our macroeconomic analysis suggests that the IMF’s focus on lowering inflation is consistent with maintaining support for market reforms. However, the magnitude of the impact of moderate inflation rates on public support is relatively small so that a critical level of support for the reforms cannot be achieved simply by keeping inflation relatively low. A higher unemployment rate has a negative effect on market support but its magnitude is also too small to consider the labor market as the main explanation for market support, as do many theoretical models. The negative relationship between unemployment and market support at the aggregate level is supported by robust evidence at the microeconomic level. Our results also show that fast privatization reduces support for the reforms, which reflects problems with the privatization process in many East European countries. Alternatively, progress in establishing working financial markets leads to more market support, although the net effect of these two indicators of structural reform on public support is negative. In addition, we find that higher per capita foreign aid is associated with stronger support for reforms, indicating the possibility of supporting the creation of market economies from outside even though the purchasing power of an additional dollar of foreign aid is relatively

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small. A higher degree of political competition fosters support for the market, which reflects the interdependencies between economic and political transformation in Eastern Europe. Finally, income inequality may have a negative impact on market support. However, the predictive power of the Gini coefficient explains only differences across countries but not differences within one country across time. Nonetheless, economic policies that generate increased inequality along with other positive outcomes must be considered carefully. With respect to the microeconomic-level results, we note that making policy recommendations based on the individual characteristics of people is problematic. An obvious policy concern is the support of the more disadvantaged groups in society, e.g., the unemployed and pensioners. Regarding the personal economic situation of people, providing resources to satisfy basic human needs such as food and clothes may also have a positive effect on support for market reforms. Raising the level of education will increase public support for the market eventually but this policy will not have an immediate impact; thus, it will not be able to boost support for reforms during the critical early phase of transition. Finally, incorporating the interest of women in the design of transformation policies will broaden the political base for support. Since we do not identify one overwhelming determinant of public support for market reforms, a package of policies is the most effective strategy for creating a market economy. A useful starting point for East European governments is to keep inflation down and to provide basic support for those citizens who lack food and shelter. Industrial countries could support these transition polices by raising the level of foreign aid per capita. Although economic transition without unemployment is impossible, and increasing unemployment lowers public support for the reforms, the magnitude of this effect is not dramatic in the early stages of transformation. The citizens in Eastern Europe seem to understand that unemployment must increase during economic restructuring. However, overly quick privatization and enterprise restructuring should be avoided, while the establishment of functioning financial markets should be promoted as quickly as possible. Hence, the debate over shock therapy and gradualism is mainly academic because our empirical results suggest that a specific combination of rapid and gradual measures will succeed in maintaining public support for the reforms. Finally, we conclude that economic and political transition are perceived to be two parts of the same package by the populace in Eastern Europe because transforming the political system to ensure free political competition raises support for market reforms. Such interdependence argues against an Asian strategy in which the creation of a market precedes the establishment of a democracy. Acknowledgments Special thanks to John Bonin for outstanding editorial input, and three anonymous referees, Jörg Breitung, Jan Fidrmuc, Michael Funke, Arik Levinson, Bernd Lucke, Robert MacCulloch, Dieter Nautz, Birgit Uhlenbrock, Jürgen von Hagen, Christian Weller, Jürgen Wolters, participants of the Eastern Economic Association Annual Conference in Crystal City, European Public Choice Society Annual Meeting in Siena and of Research Seminars at Humboldt-University Berlin, University of Bonn, Essen University, Georgetown University, University of Hamburg, and the Center for European Integration Studies for helpful comments. The usual disclaimer applies.

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Appendix Table 1 Factor analysis of market economy indicators Factor 1 Explained variance, in % Factor loadings Respondent prefers: differential incomes vs. equal Respondent prefers: private property vs. state Respondent prefers: high pay and risk vs. secure job Respondent prefers: lots of goods, higher prices vs. price controls

41 0.70 0.72 0.58 0.56

Notes. 1. The number of cases is 9782. 2. One factor is extracted by applying the usual criterion of taking factors with eigenvalues larger than 1.

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