|R sq.|0.0761|0.7565|0.5825|0.9201|0.8192|0.5790|0.9009|0.7119|
|---|---|---|---|---|---|---|---|---|
|N|149|118|54|32|22|49|31|18|
|groups|19|15|||||||
|Method<br>|RE|RE|POOLED IV<br>2SLS|POOLED IV 2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|
|Wald test Chi<sup>2</sup><br>statistics p-<br>value|0.0022|0.0000|0.0000|0.0000|0.0000|0.0000|0.0000|0.0000|
|Chow test F<br>statistics p-<br>value|0|.0000||0.8832|||0.9534||

_Note: *** significant at 1% level, ** significant at 5% level, * significant at 10% level. RE - random effects generalized least squares estimation method, POOLED IV 2SLS - pooled two stage least squares procedure with instrumental variables on panel data; robust standard errors utilized. The detailed description of all the models applied in our analyses is given in Annex 4._ _Source: OECD, Eurostat, World Bank, Heritage Foundation, IZA, own calculations._

# _<u>Model 5 – Share of workers without a legal contract</u>_

The last model that we examine is Model 5 with share of labor force employed without a legal written contract as a dependent variable, the results of which are summarized in Table 7. The results of this model are close to Models 1 and 2 (in contrast with Models 3 and 4). The explanation power of the model is solid, explaining more than 40% of variability in dependent variable on S2 and S3. However, the explanation power of the model is rather weak for S1 (Rsquared below 11%) and its fit measured by the Wald test is poor for old European subsample of S1 indicating joint insignificance of the regression coefficients. For this reason, we omit the results of the S1 sample from further analysis and discussion and we concentrate on samples S2 and S3. Their explanation power measured by the R-squared is higher for the NMS group, while their ability to describe the variability in the old European subsample is lower (see Table 7).

All the labor market institutional variables and factors related to political-economic environment of the countries proved to be significant in the model. The employment protection legislation coefficient is again positive, indicating that the excessive legal protection leads to a higher share of workers who have no legal written contract. The result is intuitive both given the variable’s literal meaning―share of workers on temporary contracts and without any legal contract, i.e. workers not protected by strong EPL―and its role as a proxy for shadow employment. It is also consistent with similar effect of the EPL in Models 1 and 2.

Other indicators show weaker effects. Level of labor taxes seems again to diminish shadow economy indicator, in this model share of workers without a contract. The same effect has a higher trade union density, as trade unions may exercise pressure on government to impose harsher penalties for non-contract workers. **Higher minimum wage seems to increase the share of workers without the contract, but only in the new EU members subsample** . Labor market policy expenditures, both passive and active, have ambiguous effects on noncontract employment.

Out of the other control variables, only fiscal freedom and business freedom seem to have a consistent―negative―effect on the dependent variable. Level of economic development measured by GDP per capita tends to reduce shadow employment, but the robustness of this outcome is limited to S2 only. Control of corruption, level of economic development measured by GDP per capita and regulatory quality all show statistically weak effects.

25