DOES ECONOMIC INTEGRATION PROCESS MATTER FOR INCOME INEQUALITY IN CENTRAL AND EASTERN EUROPEAN COUNTRIES?

Economic integration can be defined as the expansion of markets from the national to the regional or to the world level. Therefore, two channels of market integration can be determined: regional integration, for instance, within the EU, and globalization. The purpose of this paper is to investigate the impact of the economic integration process on differences in income among and within Central and Eastern European countries (CEECs). The hypotheses on 1) the economic integration relevance and 2) the mechanisms through economic integration affecting income inequality are tested with data on 10 CEECs (Bulgaria, Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia, Slovenia, Romania) for the 2000-2006 period. An unbalanced panel induces to estimate Random effects regressions and fixed-effects regressions. The results show that globalization contributed significantly to income inequality among CEECs as well as to the upward trend in income inequality within the societies of these countries, while regional integration with and within the EU did not explain considerably the changes in income distribution over the study period.


Introduction
The deepening of market (economic) integration of the Central and Eastern European Countries (CEECs) during the period 2000-2006 proceeded through two channels: regional integration within the EU and globalization. The purpose of this paper is to investigate the impact of the economic integration process on in income inequality among 18 and within the CEECs. The research addresses the following questions: 1) could European integration or globalization be a significant factor that has contributed to changes in income inequality between and within the CEECs? 2) if so, how have these two channels of market integration affected income inequality? What mechanisms have been important? Are the effects on the welfare state or the pressures of international wage and employment competition involved? These hypotheses are tested with data on 10 CEECs (Bulgaria, Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia, Slovenia, Romania) for the 2000-2006 period. The dependent variable is the Gini coefficient, a measure of income inequality. The Eurostat is a primary data source. European integration is measured as the percentage of a country's total exports that go to European Union countries or the intraregional trade share. Globalization is reflected by two measures: 1) foreign direct investment (FDI) intensity, or the average value of inward and outward FDI flows, divided by GDP; and additionally 2) trade integration, or the average value of imports and exports of goods and services, divided by GDP. The econometric models include control variables for economic development, national welfare spending and labour market. The data form an unbalanced panel, with countries contributing different numbers of observations, depending on the data availability. This problem suggests to estimate Random-effects regressions and/or fIxed-effects regressions. The small size of the sample results in insufficient degrees of freedom necessary to estimate coefficients for all the control variables. The solution is to estimate the baseline model, to add each of the other controls sequentially, and finally to estimate the model with a full complement of controls.
The structure of the paper is as follows: 1) the discussion on the mechanisms through which regional integration and globalization -two channels of economic integration -can affect income inequality; 2) the methodology; 3) the results that verify the hypotheses on the relevance of European integration and globalization for explaining the differences in income inequality among and within the CEECs; 4) conclusions.

Economic integration and income inequality
Economic integration can be defined as the expansion of markets from the national to the regional or to the world level. Therefore, two channels of market integration can be determined: regional integration, for instance, within the EU, and globalization. There are three key distinctions between these channels (Beckfield, 2006: 7-8). First, regional integration is geographically bounded, while globalization is most often meant as an intensification of cross-border flows. Second, regional integration is more strongly institutionalized than globalization. The EU requires its candidates to meet some requirements and its members to meet, for instance, the convergence criteria before joining the currency union. Third, regionalization has progressed further than globalization. Fligstein and Stone Sweet (2002) note that nearly half of all world trade occurs within the EU. The question arises how European integration and globalization influence income inequality.
Both regional integration and globalization open economies. It results in 1) changes in the employment structure, and 2) an increase in wage competition among workers. Globalization stimulates foreign investment that can benefit more capital than labour and decline union power. Scheve and Slaughter (2004) found evidence that foreign investment declines economic security among workers in industries. Economic openness can be responsible for an increase in income inequality. On the other hand, raising the volume of international trade and investment is a strong factor of growth. Liberal economics gives the highest priority to growth in an incomeinequality reducing strategy (Brady, 2003b).
There are the additional mechanisms linked to European integration, mostly to its institutional character (Beckfield, 2006). Institutional economics highlights the importance of political and institutional factors in explaining income inequality and poverty due to their impact on redistribution. Many researchers show that the welfare state reduces inequality and poverty (Blank, 2000 . European integration influences the welfare state generosity through three mechanisms. First, the convergence criteria require the fiscal discipline, and this requirement leads to cuts in social transfers. Second, EMU is concentrated on low inflation. However, low inflation benefits mostly the rich. The poor require full employment policy, not tight monetary policy (Boix, 1998;Hibbs, 1987). Third, the EU stimulates market-oriented policies, such as deregulation, privatization, tax competition. Finally, European integration is much more a "negative" than "positive' integration, or it is focused much more on the removal of barriers to trade and market regulations than on the correction of market dysfunctions (Scharpf, 1996(Scharpf, , 1999. Advocates of the welfare state blame free market for increasing income inequality. Liberal economics presents quite an opposite argument. Free market is one of fundamental factors for growth and thus for the reduction of income inequality (Brady, 2003b).
Research on income inequality and poverty is usually concentrated on three social 20 forces that drive inequality: economic development (Nielsen, Alderson, 1995Alderson, , 1997, welfare state (Brady, 2003a;Brady, Esping-Andersen, 1990; Kenworthy, 1999) and globalization or investment dependence (Alderson, Nielsen, 1999Bluestone, Harrison, 1982;Dixon, Boswell, 1996;Firebaugh, 1992Firebaugh, , 1996. The effect of regional integration has received less attention. Empirical findings presented in the literature show that the EU expands inequalities by contracting the welfare state (Boje et al., 1999) or suggest that European integration can resist globalization's effect on inequality (Moses, 1995) as well as reveal that the impact of regional integration on inequality is uneven, with certain inequalities (gender inequality) alleviated by the "regulatory suprastate" (Walby, 1999). Recently Beckfield (2006) has found evidence that European integration increased income inequality within the EU members during the period of 1973-1997, though the effect of economic integration was attenuated at the highest levels of integration.
The consequences of economic integration for income inequality in the CEECs should be also examined.

Methodology
Variables. The dependent variable is the Gini coefficient, a measure of inequality that varies from 0 to 1, where 0 is perfect equality and 1 is perfect inequality. In calculation, the Gini coefficient is multiplied by 100.
There are two basic independent variables that represent two channels of economic (market) integration: European integration and globalization. European economic integration is measured as the percentage of a country's total exports that go to the EU (25 countries), or the intraregional trade share (Frankel, 1997;Beckfield, 2006). Globali-zation is reflected by two measures: 1) foreign direct investment (FDI) intensity, or the average value of inward and outward FDI flows, divided by GDP; and additionally 2) trade integration, or the average value of imports and exports of goods and services, divided by GDP.
Control independent variables. The analysis includes: 1) GDP per capita in PPS (EU27=100) to control for the relationship between development and inequality; 2)social benefits paid by general government! (% of GDP) to investigate the welfare state effect on inequality; Additional controls to examine the mechanisms through economic integration could affect income inequality: A. variables of labour market: unemployment rate, longterm unemployment rate; female employment rate; employment rate, by highest level of education attained (% of age group 25-64 years) -primary, secondary, tertiary education; B. labour market institution -union power2 measured by workers involved in strikes per 1000 workers; C. inflation rate (HICPs) -as a goal of macroeconomic policy.
Data on 10 CEECs (Bulgaria, Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia, Slovenia, Romania) for the 2000-2006 period come from the Eurostat. Unfortunately, data on the European 1 Social benefits are transfers to households, in cash or in kind, intended to relieve them from financial burden of a number of risks or needs (by convention: sickness, invalidity, disability, occupational accident or disease, old age, survivors, maternity, family, promotion of employment, unemployment, housing, education and general neediness) made through collective schemes, or outside such schemes by government units (Eurostat's definition). 2 The number of observations on trade union density in the CEECs is too small (OECD data). integration measure are not available for Bulgaria and Romania.
Method. The data form an unbalanced panel, with countries contributing different numbers of observations depending on the data availability. This problem suggests to estimate Random-effects regressions (REM -random-effects model) and/or fixed-effects regressions (FEM -fixed-effects model). The REM preserves both between-country and within-country variations. If the independent variables are significant in the REM, it means that these variables explain both inter-and intra-country variations. The FEM differences remove all inter-country variation in subtracting each observation from the intracountry mean. The FEM can be interpreted as explaining intra-country variation and control of all time-invariant inter-country variation.
The small size of the sample (N = 10, T = 7) results in insufficient degrees of freedom necessary to estimate the coefficients for all the control variables. The solution is to estimate the baseline model, to add each of the other controls sequentially and finally to estimate the model with a full complement of controls.

Trends
The result presentation starts from the analysis of trends in the variables during the period 2000-2006. The value of the coefficient in the REM(FEM) regression and t-statistics are shown in Table 1.
Income inequality. The transformation process in the 90s resulted in an increase of income inequality in the Central and Eastern European countries. This upward trend kept strongly during the period 2000-2006.
European economic integration. The EU is the main trade partner of the CEECs. The Globalization. Both measures, the FDI intensity and trade integration (imports plus exports as a percentage of GDP), show the upward trends. The trade integration trend was especially strong. The upward trend in globalization and the downward trend in trade with the EU suggest that globalization crowded out economic integration with the EU over the study period.
Economic development. The GDP per capita very strongly increased and the unemployment strongly declined, reflecting a considerable progress in the economic development of the CEECs during the period 2000-2006.
Social benefits. The downward trend was statistically significant but not especially strong. The generosity of social policy tended to decline.
Changes in the employment structure. The upward trend was the strongest in the female employment rate. Employment rates for secondary and tertiary education had also the upward trends, while employment rate for primary education tended to decline.
Union power. The number of workers involved in strikes was completely insignificant.
Inflation rate tended considerably to decline.
The relevance of economic integration channels Table 2 shows the results of appying the random-effects and fixed-effects models to regressions of income inequality under European integration and globalization (two measures). Model 4 includes the measure of European integration (the percentage of total exports from a country sent to the EU-25) and the first measure of globalization, the FDI intensity. Model 5 includes the measure of European integration and the second measure of globalization, trade integration (imports plus exports divided by GDP). The results show that only globalization is significant in all types of models, suggesting that globalization explains differences in income inequality among the countries as well as the rising inequality within the countries. The coefficients of European integration occur to be completely insignificant in both models.
The literature points to economic development and the welfare state as the factors that are important in explaining income inequality. The results support these hypotheses rather weakly. The regressions of the Gini coefficient on GDP per capita or on social benefits show that economic development can explain differences in income inequality mainly within the countries, while social benefits do it only among the countries and weakly (Table 3). Unemployment occurred to be statistically insignificant ( Table 3).
The findings suggest that market integration affected income inequality in the CEECs in the period 2000-2006 through globalization. One should test whether these estimates of globalization effects hold up to controls. Tables 4 and 5 show the results for both measures of globalization and controls. Models 10 and 13 introduce GDP per capita, models 11 and 14 introduce spending on social benefits, Table 3.  and models 12 and 15 introduce the inflation rate. The coefficient estimate for globalization (for both its measures) remains significant after each control variable is incorporated into the model. The coefficient for GDP per capita is insignificant at the 0.05 level in all types of models, while the social benefit coefficient is very weakly significant only in the REM regression, which includes the FDI intensity and is completely insignificant in the models with trade integration. Considering inflation, its coefficient is weakly significant only in the models with trade integration. The results suggest that globalization almost fully explains the effects of both economic development and social policy on income inequality. This conclusion is supported by findings from other models (Tables 6 and 7) which show that globalization stimulated economic development (it increased GDP per capita and declined unemployment) and crowded out trade with the EU (globalization was associated with a decline in the measure of European integration) as well as trade integration was strongly associated with a decline in social benefits. Globalization affected income inequality through changes in the employment structure. There are two hypotheses how trade integration may contribute to the distributional changes (Hoffmeister, 2006). First, advanced economies specialize in the production that requires high-qualified labour. It increases the demand for skilled workers and declines the demand for unskilled labour force. As a consequence, the gap between earnings obtained by skilled and unskilled workers extends, and trade integration contributes to the income inequality increase. Second, less developed countries offer the output that requires large resources of less skilled labour force. It evokes a higher increase in low wages. Finally, trade integration reduces income inequality in these 26 countries. The results presented in Tables 8  and 9 support the first hypothesis. Opening the CEECs, on the one hand, has generated demand for skilled workers with secondary and tertiary education; on the other hand, the increasing trade integration has been associated, although very weakly, with a decrease in the employment rate for workers with primary education 3 • The data listed in Tables 8 and 9 show a strong positive relationship between globalization (both measures) and the female employment rate. The increasing participation of women in the paid labour force may affect income inequality in two ways. A higher female employment rate may lower women's average earnings (Thurow, 1987) or it may increase women's wages in middle-income households (Cancian, Danzinger, Gottschalk, 1993). The effect may depend on the selection  Alderson, 1997). The results of the REM and FEM regressions reveal a positive relationship between FDI and the female employment rate, but only for women with a secondary and especially a tertiary education 4 • The increasing participation of women in labour force, induced by globalization, has deepened income inequality in the CEECs.

Conclusions
• Globalization occurrs to be the only factor that has significantly explained the differences in income inequality between the CEECs as well as the upward trend in income inequality within societies of these countries over the period 2000-2006. • Regional integration with and within the EU did not contribute conside-rably to changes in income distribution. • The relationships between foreign investment or trade integration (the measures of globalization) and income inequality appear to be a net of statistical controls for other factors which are suggested by the economic theories as determinants of the distributional changes, including economic development and welfare retrenchment. • Globalization affected the income inequality increase in the CEECs through changes in demand for labour. Openness of the economies stimulated employment for skilled labour force. • In the short run embraced by the research, globalization induces an increase in income inequality. Whether globalization will reduce income inequality via growth in the long run, as liberal economics suggests, still remains an open question.