The extended data samples S2 and S3 allow us to run separate regressions for NMS group and old European countries. Although the estimated coefficients suggest different behavior of the two groups of countries, the results of applied Chow tests do not allow for rejection of the hypothesis of stability of regression coefficients between these two groups of countries in either of the sub-models.

**_Table 7. Results of Model 5– dependent variable CONTRACT_**

||S1 – Mo<br>|del 5.1<br>||S2 – Model 5.2<br>|||S3 – Model 5.3<br>|<br>||
|---|---|---|---|---|---|---|---|---|---|
||Total|Old Europe|Total|Old Europe|NMS|Total|Old Europe|NMS||
|EPL|4.1585 ***|0.0980|562.1071 ***|653.9701 ***|499.0793 ***|2.7880 **|6.5737 ***|6.9879|***|
|MW|-0.5562 *|-0.2438|-0.1224|-0.0793|4.6800 ***|-0.0925|-0.4403|6.2950|**|
|TU|-0.1036 *|-0.0752||||-0.1006 *|-0.0865 **|-0.5563|***|
|TAX|_0.1701_*|0.0614|-0.3391 **|-0.4405|-0.8808 ***|-0.1898 **|-0.2152|-0.2119||
|LMPA|5.5891|-6.2919|-33.2684 **|-26.3724|114.2258 ***|-20.5066|-15.8073|44.6655||
|LMPP|-1.3019|4.9171|13.3768 **|17.5201|49.1185|-1.8657|-0.3121|-160.8801||
|lnGDPPC|4.7619 **|-3.0364|-4.6410 **|-4.0338|-7.8942 ***|-1.5095|-8.8021|0.9432||
|FISF|0.0340|-0.0020|-0.3544 ***|-0.2476|-0.2773 **|-0.2135 ***|-0.1099|-0.4078|**|
|BUSF|-0.0075|0.0354 **|-0.2533 ***|0.0556|-0.5684 ***|-0.0381|0.1100 *|-0.2582|*|
|CORR|-2.9826 ***|-0.6461|4.4729 *|4.5274 *|1.2196|5.4242 **|4.0122 *|3.7078||
|REGQUAL|1.9812|0.0067|-4.1349|-10.8420|6.8003 **|-4.1791|2.2713|-11.2454||
|constant|-17.8050 **|19.8145|70.7803 ***|46.6566 **|93.1514 ***|35.6348 ***|27.7419 ***|61.5898|***|
|R sq. Within|0.3339|0.1382||||||||
|Rsq. Between|0.1076|0.0676||||||||
|R sq.|0.1058|0.0612|0.6150|0.6108|0.9269|0.4100|0.5604|0.7847||
|N|146|115|53|31|22|49|31|18||
|groups|19|15||||||||
|Method|RE|RE|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV<br>2SLS|POOLED IV|2SLS|
|Wald test<br>Chi<sup>2</sup>statistics<br>||||||||||
|p-value|0.0000|0.1843|0.0000|0.0000|0.0000|0.0000|0.0000|0.0000||
|Chow test F<br>statistics p-<br>value|0.15|82||0.9462|||0.9994|||

_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._

# **6.** **<u>Conclusions</u>**

Several estimation approaches for different data samples and explanatory variables were used in this paper to analyze the impact of labor market institutions on the development of shadow production and employment in European countries. The presented results for different model specifications show that the most robust estimation outcomes come from specifications that use as dependent variables the shadow economy as percentage share on overall official GDP, the share of labor force not contributing to the pension system and the share of labor force employed without a legal written contract. Models explaining the share of labor force employed in small firms with fewer than ten employees or being self-employers do not offer robust results, as the two indicators proxy shadow employment only weakly and are influenced by other factors and patterns of development. Our findings also confirm that availability of relevant data related to the shadow economy and employment for European 26