## **Box 5.  Ethnicity, Earnings, and Occupational Segregation**

An issue of great political importance in the Baltic countries is that of discrimination against ethnic minorities. A critical problem in evaluating this issue is that the available data do not contain information on state language skills, which are likely to be correlated with ethnicity. Bearing this in mind, the average differentials are sizable nonetheless. According to LFS 2002 data, in which ethnicity is self-reported, ethnic Latvians’ average net earnings were 10 percent higher than those of other ethnic groups (mainly Russians). This can be compared to a 16 percent differential found in Estonia and 9 percent - in Lithuania (using 2000 data).

Despite the low levels of occupational segregation amongst ethnic groups in Latvia, segregation of ethnic groups by economic activities is substantial. According to a dissimilarity index measure of segregation, at 0.21 segregation in Latvia is less strong than in Estonia but larger than in Lithuania. Table 8 summarizes the most pronounced horizontal segregation patterns. All three countries having a relatively low share of minority employees in public administration, and relatively high share in transport and communications (Appendix Table 27 provides details for Latvia). In contrast with occupational segregation, there is no clear evidence that minorities are concentrated in lowwage sectors. Segregation with respect to ownership sector is found only in Latvia, where 35 percent of nonLatvians and 49 percent of Latvians are employed in the public sector.13 Finally, in all three countries a much larger proportion of minorities than of native employees have the advantage of working in the capital city, where the wages are higher.

It is of policy interest to compare gross ethnic wage differentials and unexplained wage differentials with those experienced in the other Baltic countries (see Table 10 and Appendix Table 31). The gross differential and unexplained gap are largest in Estonia, while the Latvian and Lithuanian gaps are comparatively modest. Only in Lithuania can part of the gross ethnic wage differential be explained by observed employee characteristics, and this part is small when occupation is not controlled for. After accounting for major occupational groups and firm size the unexplained gap narrows by 30 percent in Estonia, by more than 40 percent in Lithuania, and fully disappears in Latvia. This suggests that occupational segregation is responsible for a substantial part of the ethnicity effect on earnings. The residual gap in Estonia and Lithuania has to be ascribed to unobserved characteristics and finer occupational segregation than accounted for here.

**Table 10.  Gross wage Differentials**<sup>**a**</sup> **and productivity Differentials**<sup>**b**</sup> **between Native Employees and Ethnic Minorities. Baltic Countries, 2000 – 2002. Percent**

||**Gross wage**<br>**differential**|**Productivity differential**<br>**(without occupation controls**<sup>**c**</sup>**)**|
|---|---|---|
|Estonia (2000)|12.2|-4.6|
|Latvia (2000)|3.3|-2.6|
|Latvia (2002)|10.2|-2.1|
|Lithuania (2000)<br>|8.7<br>|1.8<br>|

_Notes_ :<sup>a</sup> These differentials are based on mean log wages of the two groups rather than mean wages.<sup><u>b</u></sup> Differential in (geometric) mean predicted wages of males and females, using earning function estimated over pooled sample without ethnic dummy; known also as explained pay gap.<sup>c</sup> Sector of economic activity is controlled for. _Sources:_ Calculations based on LFS data.

# **Local unemployment and wages**

One of the commonly used methods of measuring labor market flexibility is to estimate so called wage curve: the responsiveness of wages to regional unemployment rates at job locations (see Blanchflower and Osvald (1994). This methodology involves calculating the relationship between wages and unemployment levels, referred to as elasticity. This calculation measures the responsiveness of wages due

> 13  Only hired employees are considered in this analysis.

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