39. Regressions were run on the pooled data set comprising observations from all EU8 countries (with dummy variables for each country), as well as separately for each country (with dummy variables for regions in the case of the Czech Republic, Hungary, and Poland). Regression coefficients for the variables used in the analysis are presented in Table 11.

**Table 11: Regression Analysis: (log) Equivalized Disposable Income**

||||||**Coefficient**|||||
|---|---|---|---|---|---|---|---|---|---|
||**EU8**|**Slovenia**|**Czech**|**Slovakia**|**Hungary**|**Estonia**|**Poland**|**Lithuania**|**Latvia**|
|**Demographic composition of**|**household:**|||||||||
|Share of 0–17 yr olds|-0.635***|-0.295***|-0.486***|-0.531***|-0.610***|-0.518***|-0.690***|-0.730***|-0.627***|
|Share of 18-64 yr olds|-0.088***|0.106***|0.019|0.061***|-0.111***|-0.241***|-0.136***|-0.209***|-0.205***|
|Share of 65+ yr olds|||||_omitted variable_|||||
|**Employment status:**||||||||||
|Share of 18+ unemployed|-0.785***|-0.588***|-0.508***|-0.805***|-0.641***|-0.875***|-0.842***|-0.981***|-1.005***|
|Share of 18+ retired|0.128***|0.264***|0.074***|0.095***|0.208***|-0.071**|0.187***|0.067|-0.271***|
|Work intensity status|0.166***|0.196***|0.184***|0.146***|0.199***|0.272***|0.135***|0.277***|0.216***|
|**Education: share of 16+ with:**||||||||||
|Primary education or less|||||_omitted variable_|||||
|Lower-secondary|0.007|0.099***|-0.039|0.027|0.065**|-0.005|0.017|-0.086**|0.004|
|Upper-secondary|0.253***|0.358***|0.132|0.214***|0.305***|0.127***|0.283***|0.090**|0.235***|
|Post-secondary / tertiary|0.727***|0.811***|0.470***|0.519***|0.735***|0.394***|0.838***|0.488***|0.645***|
|**Regression constant**|7.9***|8.1***|8.0***|7.5***|7.6***|7.5***|7.7***|7.0***|7.2***|
|||_country /_|_regional dumm_|_ies included in r_|_egression specificatio_|_n, but excluded_|_from output repor_|_ted here_||
|**Number of observations**|59,161|7,482|5,603|7,691|4,642|4,266|14,896|9,478|5,103|
|**R-squared**|0.42|0.45|0.37|0.37|0.39|0.37|0.35|0.41|0.32|

_Significance level of reported coefficients: 0.01 - ***; 0.05 - **; 0.1 - *_ 40. In EU8 countries overall (as well as in each country), we find disposable incomes to be negatively correlated with share of household members aged 0-17 years.<sup>17</sup> Correlation of incomes with share of people aged 18-64 years is positive in Slovenia, Slovakia, and the Czech Republic (not statistically significant in the case of the latter), but negative in other countries. Employment status is a strong predictor of welfare in all EU8 countries, with disposable incomes negatively correlated with share of unemployed household members, and positively correlated with work intensity status. The size of the association is relatively more pronounced in the Baltic countries, which is consistent with our earlier finding regarding the relatively smaller size of redistributive public transfers in these countries. Similarly, disposable incomes are positively correlated with level of educational attainment of household members in all countries, with the “premiums” associated with tertiary / secondary education highest in Slovenia and Poland (countries with the highest share of population with primary education or lower).

# **Differences in human capital and labor force participation rates across regions explain a large part of the observed differences in living conditions within countries**

41. Controlling for differences in demographic composition, employment, and education status across regions, how important are unobservable location-specific factors in explaining regional differences in living standards? The regression coefficients of virtually all regional dummies included in the country-level regressions are statistically significant, indicating the presence of unexplained region-specific factors impacting living standards. However, as shown in Table 12, after one has accounted for differences in income levels attributable to differences in work status, demographic

> 17 This is not quite as obvious a finding as may initially appear, since equivalized incomes in EU countries incorporate very high equivalence / economies-of-scale adjustment factors.

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