The preeminence of SEG among the key determinants of poverty in Latvia is further illustrated by the significance of “ _EMPLOY_ ” for employment status of household heads. This correlate has a parameter significantly different from zero at the 95% level in urban and rural areas. Its marginal effect is in the magnitude of 13% in rural areas and 11% in urban areas.<sup>47</sup> Moreover, the distribution of welfare across employment status of household heads has large variance. While the headcount index is about 14% at the national level, the poverty rate for unemployed is about 40%, significantly above the rate recorded for the employed income group. The welfare contrast between employed and unemployed was already apparent in the mid 1990s, where the headcount for unemployed then, exceeded 38% (World Bank [2000a]). The persistence of this contrast in the late 1990s may suggest that the benefits of growth accruing to this vulnerable group were not significant, reflecting the fact that growth may not have led to significant creation of jobs.

In a context where most income is derived from wages and salaries, the significance of unemployment is not counterintuitive. Poverty is in fact directly related to unemployment in urban and rural areas in Latvia. The significance of this regressor is illustrated by Figure 8. The figure provides estimates of the conditional probability of being poor, plotted on the _yaxis_ against increasing ratio of unemployment on the _x-axis,_ holding other regressors constant at their mean values. The urban probability plot refers to the dark curve; the rural probability plot refers to the heavy and gray curve. The slope of these curves is positive, suggesting that the probability of being poor rises with unemployment ratio. However, for the same unemployment ratio, the event probability of being poor is uniformly higher in rural areas, again, reflecting the urban-rural poverty and unemployment gaps. The probability of being poor ranges from 17 to 45% in rural areas, and varies between 0 and 5 % in urban areas over the support of unemployment ratio.

When conditioned upon unemployment ratio, the rural predicted probability of being poor is almost linear. It rises almost uniformly for increasing unemployment ratio. The near linear pattern may suggest that the chances of being poor when one is unemployed are higher in rural areas, probably reflecting the limited opportunities and income generating activities there. By contrast, the urban predicted probability has a curvilinear shape with extremely low probability over the support of unemployment. That curvilinear shape is partly illustrated by the widening urban-rural predicted probability gaps, especially towards the end of the support of the hypothesized unemployment ratio, where the gap is about 40 percentage points.

There are other correlates with large marginal effects on the event probability at the regional levels. In particular, these include the burden of age dependency, employment status, housing amenities. Here, we focus on the latter, which as pointed out earlier has one of the largest Chi-square statistics, and has been identified in the past to be significant in Transition Economies (World Bank [2000a]). The parameter estimate of housing amenities variable derived as the sum across all facilities available at the household level is a significant determinant of poverty in urban and rural areas.<sup>48</sup> In spite of its relatively low marginal effect

> 47 The significance of this predictor is not specific to Latvia, however. A number of labor market-related variables— head is inactive, unemployed or number of unemployed in households--- have been found to be significant determinants of poverty in Eastern Europe and Former Soviet Union countries in most of the 1990s, reflecting the fact that unemployment has been the most visible signs of the social costs of transition (Braithwaite, Grootaert and Milanovic [2000]).

> 48 Facilities and amenities available at the household level include: electricity, water supply, sewerage, toilet, hot water supply, central heating, shower or bath, separate kitchen, gas from network, gas from container, electric oven, and phone line.

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