dummy for “spouse does not live currently in the household” (this category does not include spouses who migrated for work). In Model 3, I add to the base specification a dummy for “spouse did not work in the last 14 days”. The estimated coefficient on the spouse’s absence is negative and statistically significant in the regressions for men, and positive but not significant in the regression for women. The positive coefficient in the regressions for women result suggests a weak added worker effect (AWE). The estimated coefficient on the main variable of interest (an interaction between “war cohort” and “living in more affected area”) is positive and statistically significant in the regressions for women, although it is smaller in absolute value than in the regressions for the whole sample.<sup>24</sup> Thus, the women from the war-cohort who also lived in the war affected regions in 1992 are more likely to be employed in 2007. These results are robust to the use of alternative subsamples and controls for migration of household members, unemployment of the household head, and absence of a spouse from a household. These results indicate that young women, who received fewer years of schooling as a result of the war as documented earlier in this paper surprisingly, are more likely to be employed in 2007. This higher workforce participation by women in the regions that had a deficit of males is consistent with findings by Acemoglu et al. (2004) and Menon and van der Meulen Rodgers (2011).

# _Wages and Conflict_

Next, I turn to the evaluation of the effect of conflict on wages. Table 9 presents results from Tobit regressions with raion-level fixed effects. Fixed effects enter regressions as a full set of raion-level dummy variables. The dependent variable is the natural logarithm of an individual’s monetary and in-kind wages from his or her main occupation (the occupation where the individual reported the highest number

> 24 I also tested the effect of having relatively fewer males as compared to women in the working age group on labor market participation. For this test, I used two raion-level sex ratios of men to women for 1989. The first ratio is for the age group 20-49 and the second one includes ages 15 to 64. The age groups cut-off points are based on the cut-offs for the population numbers published by the State Statistical Committee of Tajikistan and based on the 1989 Census. The linear probability regressions are estimated with robust standard errors that control for heterogeneity at the raion level to control for effects that are common for individuals living in the same community. Unfortunately, I can not use fixed effects at the raion level in this model as the sexratio variables are available only at a raion level and is constant for all observations in a particular raion. The estimated coefficient on the sex ratio for the 20-49 year olds has a positive impact on the employment by men and women in 2007, but is significant only in the regressions for the sample of men (results not reported), suggesting that an increase in the number of men relative to women prior to the war had a positive and significant effect on the labor force participation of men.

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