First, we constructed a panel of nineteen European countries and used data for period 20002007 (basic data sample――S1‖).<sup>27</sup> Out of all the countries in the panel, fourteen are old member countries, one is Norway, which we classify as an old member country for purposes of this paper, and remaining four countries are the NMS. The source of the data is mainly the OECD and partly also Eurostat, World Bank and Heritage Foundation. However, as this sample covers only four NMS (the Czech Republic, Slovakia, Hungary and Poland) we expanded our analysis to other NMS as well in the second, extended data sample (―S2‖). The panel consists of twenty-eight countries, twelve of which are the NMS.<sup>28</sup> Yet, the availability of relevant data is a serious obstacle. Several OECD variables had to be replaced by less accurate indicators provided by the Eurostat. Moreover, the necessary set of indicators is available for a shorter time period of 2006-2007 only. The third sample we use in our analysis (―S3‖) consists of twenty-six countries, ten of which are the NMS.<sup>29</sup> The time period concerned is years 2003 and 2007. The source of the data is mainly the OECD and partly also Eurostat, World Bank and Heritage Foundation, similarly to the first sample. Furthermore, we extended OECD data for information from IZA database, which includes all the OECD measures of labor market institutions for the non-member countries of Central and Eastern Europe.<sup>30</sup> Given the limited amount of data available, the second and the third samples are used for robustness checks mainly.

We examine the impact of institutional factors on five indicators of shadow production and employment: shadow economy as percentage share on overall official GDP ( _SHEC_ ), share of labor force in unregulated self- and wage-employment measured by share of labor force not contributing to the pension system adjusted for the unemployment rate ( _CONTRIB_ ), share of labor force employed in small firms with less than ten employees ( _LESS10_ ) or being selfemployers ( _SELFEMPL_ ) and share of labor force employed without a legal written contract ( _CONTRACT_ ).<sup>31</sup> The shortcomings of the four latter indicators were already described in previous part of our paper. Moreover, utilization of the first mentioned dependent variable is also partially problematic because some of the independent variables we use (or similar measures to those we use) were also utilized as elements in the MIMIC estimation of the shadow economy.<sup>32</sup> As a result, estimation based on this dependent variable might bias the results to certain extent. Still, as shown in Friedman et al. (2000), utilizing these data does not change the nature of general findings when compared to results obtained for data estimated by other methods. But once again, no better indicators of shadow economy in comparable methodology are available. Still, one has to bear these limitations in mind when viewing our results.

> 27 Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, and United Kingdom.

> 28 Austria, Belgium, Bulgaria, Czech Republic, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Romania, and United Kingdom.

> 29 Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Romania, and United Kingdom.

> 30 For details on methodology see Lehmann and Muravyev (2009).

> 31 For description of data sources and discussion of information relevancy of these indicators see Section 1 and Annex 3.

> 32 This method estimates the size of the shadow economy from both likely causes and effects of the informal activity. The underlying variables comprise the size of the government, the unemployment rate, government effectiveness, the GDP per capita, currency (M0 over M1), the growth rate of GDP per capita, the labor force participation rate, the fiscal freedom index, the share of direct taxation, the business freedom index, the growth rate of total labor force (Schneider et al., 2010).

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