Firms and wage inequality in Central and Eastern Europe

https://doi.org/10.1016/j.jce.2020.08.002Get rights and content

Highlights

  • We show that, unlike in many other advanced economies, wage inequality levels have decreased in almost all CEE countries using use large linked employer-employee data between 2002 and 2014.

  • Wage inequality reductions resulted from disproportionately large increases in wages at the bottom of the wage distribution, and from decreases in between-firm wage inequality.

  • We further find that the declines in wage inequality were driven by large wage structure effects that compensated for changes in the composition of workers.

Abstract

We use large linked employer-employee data to analyze wage inequality patterns in Central and Eastern European (CEE) countries between 2002 and 2014. We show that, unlike in many other advanced economies, wage inequality levels have decreased in almost all CEE countries. These reductions in wage inequality resulted from disproportionately large increases in wages at the bottom of the wage distribution, and from decreases in between-firm wage inequality. We further find that the declines in wage inequality were driven by large wage structure effects that compensated for changes in the composition of workers.

Introduction

The issue of increasing income inequality is being publicly debated in most OECD countries. Many of the questions raised in these discussions center around the extent to which changes in wage inequality levels are driving income differentials. Much of the existing literature on this topic has focused on firm-level determinants, and has recognized the important role of inter-industry and firm-level wage differentials (Abowd et al., 1999; Du Caju et al., 2010; Krueger and Summers, 1988; Martins, 2004). We know far less about how between-firm wage inequality levels change over time, and whether firm-level factors have contributed to the increases in the wage inequality levels observed in many OECD countries. This paper contributes to this debate by investigating the workplace features that are likely to drive wage inequality, and how it changes at different points of the wage distribution.

While there is extensive research on recent determinants of wage inequality in the US, Germany, and many other advanced countries, this paper focuses on Central and Eastern European (CEE) countries. CEE countries are interesting not only because there is little comparative evidence on recent changes in their wage structures, but also because the countries in this geographical region have experienced similar wage inequality trends. While the transition from a socialist to a market economy was associated with increasing wage dispersion (Brzezinski, 2018), we show that the wage patterns continued to change in the period that followed. Specifically, we find that whereas wage inequality levels further increased in many advanced countries in the 2000s, they stabilized or declined in Central and Eastern Europe during this period.

There have been several institutional and economic changes in the region that likely contributed to the observed changes in wage inequality. These changes, which we discuss in detail in Section 3, involved reforms of labor codes that increased workers’ bargaining power, increases in minimum wages, and large migration outflows to Western European countries. We argue that all of these developments had the potential to reduce wage inequality. There is a broad consensus that an increase in the minimum wage reduces wage inequality, as both its direct and its spillover effects are concentrated at the lower end of the wage distribution (Autor et al., 2016; Cengiz et al., 2019; DiNardo et al., 1996). According to wage bargaining models, workers bargaining power and workers outside options determine wages (Pissarides, 2000). Therefore, the increase in workers outside options due to the opening of Western labor markets should have led to an increase in workers wages in the CEE countries. These increases were likely concentrated at the bottom of wage distribution, as the demand for migrant workers was largely limited to low-skilled jobs (Black et al., 2010).

This paper has three main objectives. First, we aim to present a clear picture of the changes in the wage dispersion patterns in post-transition CEE countries between 2002 and 2014 using harmonized, comparative data from a large, linked employer-employee dataset of the European Structure of Earnings Survey (ESES). We study both the variance of wages and the quantiles of the wage distribution. Second, we intend to analyze the role of firms in determining wage inequality, and to examine how much of this inequality is due to wage differentials arising between firms, and to within-firm wage inequality. Third, we investigate the potential micro-level factors associated with higher or lower levels of wage inequality, and particularly the drivers of the observed decrease in wage inequality during the 2006–2014 period.

Our results suggest that during the study period, wage inequality levels decreased in most CEE countries, especially in the Baltic states and Romania, where the initial wage inequality levels were the highest in the region. In these countries, the largest increases in real wages occurred at the bottom of the wage distribution. This may be related to the fact that those countries experienced the largest migration outflows and minimum wage increases during the study period, as argued above. Czechia, where the wage inequality level remains the lowest in the region, was the only CEE country that experienced a (slight) increase in wage inequality, which was observed both at the lower and the upper part of the wage distribution. Czechia also had the smallest migration outflows in CEE, and its minimum wage expressed as a fraction of the average wage decreased considerably.

We further show that the differences in the variance of wages across the CEE countries were primarily driven by the differences in the between-firm component of wage inequality (and, to a lesser extent, by wage inequality within firms). We gain additional insight into the determinants of wage inequality by applying recentered influence function (RIF) regressions following Firpo et al. (2018). We show that workplace characteristics played an important role in wage inequalities; and that of these workplace characteristics, the levels of education and the ages of an employees co-workers were as crucial as her/his occupational and sectoral affiliation. Decomposition of the changes shows that reductions in wage inequality in the region between 2006 and 2014 were largely attributable to wage structure effects (changes in the wage premia paid for individual- and firm-level characteristics, as well as in the intercept), rather than to composition effects (changes in covariates). In line with Firpo et al. (2018), we find that composition effects increased inequality, as the gains were greater at the top of the wage distribution. However, unlike in the US, we do not see polarization in wage growth, as the changes in workers returns to wages were concentrated at the bottom of the wage distribution, and thus led to decreases in inequality.

Section snippets

Literature review

Our paper is related to two main strands of literature. The first strand is comprised of studies on changes in wage inequality and their determinants. Some of the most important works on this topic include Autor et al. (2006); Autor et al. (2008) for the US; Fortin et al. (2012) for Canada; Dustmann et al. (2009) for Germany; and Machin (2016) for the UK. This literature has looked at the macro-level drivers of wage inequality, and has examined how trade and labor market frictions,

Institutional and economic background

In the early 2000s, the CEE countries had not yet completed the transition from having a centrally planned economy with artificially low levels of wage inequality to having a capitalist, market-based economy.1

Data

We use repeated cross-sectional data from the European Structure of Earnings Survey (ESES) for the years 2002, 2006, 2010, and 2014. The ESES is a large matched employer-employee dataset provided by Eurostat. It includes information on workers earnings, and on their individual-, job-, and firm-level characteristics. We use data for the following nine CEE countries: Czechia, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovakia, and Bulgaria. We additionally draw on ESES data for the

Methodological approach

Our analysis is carried out in two main steps. First, we analyze levels of and changes in wage inequality in each country over time, discussing changes at the mean and at the tails of the wage distribution. We also determine the respective contributions of the within-firm component and the between-firm component to total wage inequality. In the second step, we investigate the determinants of the levels of wage inequality, as well as the changes in wage inequality, over time.

We start the first

Overall wage dispersion and its changes

The results show that levels of wage inequality varied substantially across the CEE countries (Table 2). In 2014, the lowest wage inequality levels were observed in Czechia and Slovakia (where the variance of log wages amounted to 0.23), while the highest wage inequality level was observed in Romania (0.36). When we compare the wage inequality levels in the CEE countries to those in the more advanced European countries (Table F), we see that the levels in Czechia and Slovakia were similar to

Conclusions

Using harmonized linked employer-employee data, we analyzed changes in wage distributions in Central and Eastern European countries. We found that in all but one of these countries, wage inequality decreased between the early 2000s and the mid-2010s. Czechia, which still has the lowest levels of wage inequality in the region, was the only CEE country that saw a slight increase in wage inequality during this period. The reduction in wage inequality occurred mainly in the lower part of the wage

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    This paper has benefited from the financial support provided by the National Science Center, Poland (DEC-2013/10/E/HS4/00445) and by the World Bank Group (FY2016 DGF Network for Jobs and Development-DGF File: 502916-05). This paper is also part of the project “Migration And Labor Supply When Culture Matters”, financed by French National Research Agency (ANR-18-CE26-0002, AAPG2018). We acknowledge French ANR for financial support. We would like to thank Peter Orazem, Carl Singleton, the participants of the 2018 EALE, 2018 IZA World Labour conference, the 2018 HSE/IZA workshop, and the 2019 IAAEU seminar for their comments and remarks. We also gratefully acknowledge use of the Python/Stata template provided by von Gaudecker (2014). This paper uses Eurostat data. Eurostat has no responsibility for the results and the conclusions, which are those of the authors.

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