The regression coefficients are estimated using the generalized two stage least squares random-effects instrumental variables regression estimation procedure (models 1.1, 3.1-5.1), two stage least squares estimation procedure with instrumental variables on cross-sectional samples (models 2.2 and 2.3) and two stage least squares estimation with instrumental variables on pooled panel data (for models 1.2, 3.2-5.2 and 1.3, 3.3-5.3). The feasibility of utilization of these approaches was tested by Durbin-Wu-Hausman tests (which were replaced by xtoverid test procedure in Stata application, introduced by Schaffer and Stillman, 2006, for testing coefficients estimated in the RE and FE panel estimation procedure in case that covariance matrix in Hausman test was not positive definite) and Breusch-Pagan Lagrange Multiplier test for presence of random effects.

The regression equation has following form for all samples: _X ti = α + β1 EPLti + β2 MWti + β3 TUt + β4 TAXti + β5 LMPAti + β6 LMPPti +_ _+ β7 ln GDPPCti + β8 FISFti + β9 BUSFti + β10 CORRti + β11 REGQUALti + εti (1),_ where _X_ takes the form of _SHEC, CONTRIB, SELFEMPL_ , _LESS10,_ and _CONTRACT_ in consequent regressions (Model 1, 2, 3, 4 and 5 respectively). The detailed description of all the models applied in our analyses is given in Annex 4.

The independent variables and their expected effects were described in the previous section. In our samples S1 and S3, we used the OECD’s employment protection legislation index, version 2 ( _EPL_ ). In the sample S2, this variable was replaced by inverse value of indicator of labor freedom as the employment protection index is not available for non-OECD countries over a longer time period. Minimum wage ( _MW_ ) is a cluster variable constructed according to minimum wage level as a share of median wage in the economy in the basic sample S1 and according to minimum wage level in purchasing power parities in sample S2 and S3. The trade unions’ power is represented by the trade union density as percentage of all workers in the economy ( _TU_ ). This variable was omitted in sample S2. Tax system consequences are reflected by total tax wedge on labor income in samples S1 and S3 ( _TAX_ ). In the extended sample S2, this variable was replaced by implicit tax rate on labor. Finally, to reflect the influence of labor market policies, expenditure on active ( _LMPA_ ) and passive labor market policies ( _LMPP_ ) as percentage share of official GDP per percentage point of unemployment were included. Both variables on labor market policies expenditure were instrumented.<sup>33</sup> Other variables describing country’s political-economic environment needed to be covered too to control for their potential effects besides the labor market factors that are in main focus of this paper. First, we control for level of country’s economic development by adding the variable GDP per capita in purchasing power parities ( _GDPPC_ ). In line with the previous research, the variable is represented in logs. Furthermore, two more variables reflecting the degree of regulation in other fields apart from the employment protection were added: Fiscal freedom indicator has an inverse relationship to the overall tax burden imposed by government ( _FISF_ ).<sup>34</sup> Business freedom is a quantitative measure of the ability to do business and has an inverse relationship to the overall burden of regulation as well as the efficiency of government in the regulatory process ( _BUSF_ ). Finally, informality might be also affected by political factors such as control of corruption in the country or regulatory quality. To account

> 33 These variables might be endogenous because they relate the expenditure to the actual rate of unemployment, potentially affecting the decision about turning informal. For this reason we instrumented these variables by new variables relating the expenditure to the average unemployment rate in 5-year period before the actual year. 34 Construction of this indicator (described in Annex 3) should guarantee existence of no colinearity between this variable and variable _TAX_ .

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