which was about 19.5% for households with no elderly members aged 65 and above increased to 56.8% for households with at least three elderly members in Hungary. Similar results were derived for other countries (Braithwaite, Grootaert and Milanovic [2000]). However, household size and composition in Transition Economies are markedly different from that in other developing countries, particularly Sub-Saharan African countries, which have higher dependency ratios; and it may be worth investigating how the changing household structure interplays with poverty in the medium to long run.<sup>41</sup> Geographical regions (to account for spatial effects), household amenities, household ownership of assets and durable goods, and unemployment are also significant. These correlates have large Chi-Square and their estimated parameters are significantly different from zero at the 95% confidence level (see Table A.8 in Annex). In particular, the unemployment ratio and its quadratic form are strongly significant with low standard errors for their parameters.<sup>42</sup> The significance of the quadratic form further emphasizes the preeminence of job creation and promotion of growth strategies with high employment generating opportunities, which call for significant reduction in the time lag between output growth and employment growth, however. Yet evidence from other transition economies suggest that output recovery have not always led to immediate employment recovery; and in some cases, including among the successful reformers, the lag has been quite long (World Bank [2000b]).<sup>43</sup> The reduction in lag, and hence increased job creation and employment growth will depend on the speed, and successful implementation of reforms and labor market adjustments, to among other things achieve flexibility and movements across sectors.

The significance of the quadratic expression further supports the non linear relationship between unemployment and poverty. This non linearity could reflect the persistence of a number of structural distortions on the labor market, especially in urban areas where the non linear relation is more pronounced (Figure 8).<sup>44</sup> The non linear pattern and logistic shape of the urban probability, which is uniformly less than 5% over the support of unemployment ratio also reflects the structurally higher rural unemployment rates in Latvia. Though counterintuitive in light of findings from most other developing countries which have higher urban unemployment rates, the result is consistent in Latvia where labor market attachments of household heads and other household members were singled out as key determinants of welfare in urban areas (World Bank [2000a]).

**Figure 8: Predicted probability of being poor by unemployment rates**

> 41 Indeed the burden of age dependency is extremely high in Sub-Saharan African countries, where age dependency ratios exceeding 100 are not uncommon, and reflect the relatively large household size. Empirical evidence has shown that it is a strong determinant of poverty (Lipton [1983], Glewwe [1991]).

> 42 This further supports earlier studies, which found unemployment to be strongly correlated with poverty in Latvia (World Bank [2000a]).

> 43 In Hungary for instance, the number of jobs in 1997 was 30% less than in 1989, despite the rapid recovery of output to its pre-transitional levels. The slow recovery of employment is not specific to Transition Economies, however; evidence suggest that the adjustment process leading to the reduction in time lag exceeded 15 years in the case of Spain.

> 44 These distortions, most of which are the legacy of the socialism era, include overstaffing of state owned enterprises, labor market regulation and wages rigidities, and especially at the higher income bracket range. However, as part of the reform process, Latvian authorities have been implementing a number of adjustments to the labor market, particularly to achieve more flexibility in wage setting. This has particularly been reflected in the more rapid increase in wages for skilled workers with higher education, by over 23% between 1997 and 2000 (see Republic of Latvia, 2003).

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