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I would like to thank Celine Allard, Costas Christou, Aurelijus Dabusinskas, Pawel Gasiorowski, Albert Jaeger, Bikas Joshi, and seminar participants at the IMF for helpful comments and suggestions. I am responsible for any errors.
Labor productivity is included in Babetskii’s wage specification as a control variable but enters with a not significant and wrong-signed coefficient. His selected group of NMS does not include Bulgaria and Romania. The analysis uses quarterly data for the period 1995-2004.
The only exceptions are represented by the unemployment rate series from the IMF’s World Economic Outlook (WEO) database and the wage flexibility index from the World Bank’s Doing Business indicators.
In the text below, we refer to the following regional groups among NMS: CEE4, comprising the Czech Republic, Hungary, Poland, and the Slovak Republic; and the Baltic countries, comprising Estonia, Latvia and Lithuania.
Assuming that domestic demand and private consumption deflators grow at the same rate, this result implies an increase in the terms of trade, that is, an increase in the price of exports with respect to imports, which is consistent with the increase in the technology and human capital content of transition countries’ exports during the convergence process.
For the cross-country sample, the real wage is defined as the nominal wage deflated by the GDP deflator. According to the Eurostat definition, the nominal wage is the remuneration in cash paid by the employer during the reference year, before tax deductions and social security contributions payable by wage earners and retained by the employer. All bonuses, whether or not regularly paid, are included. Severance payments, as well as payments in kind, are excluded.
Labor productivity is defined as GDP at 1995 market prices per person employed, according to Eurostat.
All variables are in logs.
The residual of the long-run wage equation is found stationary and, in line with the Granger representation theorem, is entered in the empirical wage equation together with the short-run dynamics. However, the power of the test is affected by the small time dimension of the sample, which also imposes a parsimonious specification with homogeneous dynamics.
Other control variables are added to the baseline specification (including the activity level, excess demand for skilled workers, tax wedges, minimum wages, and the World Bank’s “Employing Workers” indicator as a measure of labor rigidity). Although all these variables are found to have a wage-push effect, as suggested by the literature, lack of a sufficient time span for most indicators hampers the statistical reliability of these results, which are therefore omitted.
Results are robust to specifications allowing for lags of the dependent variable and the regressors.
Although the empirical analysis uses the Eurostat database for consistency, official statistics from the national authorities may offer a different picture on countries’ wage setting behavior, as, for example, in the case of Poland, where national figures for real wage growth for 2006-07 are well above the Eurostat ones. As mentioned in Section III.A, these discrepancies could be due to the different coverage of the labor statistics (labor survey versus registered employment data) and the choice of the deflator (GDP-deflator versus CPI). Therefore, results for equilibrium real wages should be treated with caution.
“Wage growth in the public sector should be kept strictly in compliance with labor productivity growth, since wages in the public sector have a signaling effect for the private sector” (Ministry of Finance of the Slovak Republic, Convergence Programme for 2007-2010, November 2007, p. 9).
“Excess demand” for skilled workers is defined as the difference between the percentage share of workers with tertiary education in unemployment and that one of workers in employment, considering only workers between 15 and 64 years old (World Bank, 2007).
See Berg and Cazes (2007).