100 CHAPTER 5
Our approach belongs to the first group of studies, those using panel data. Owing to data constraints (explained earlier), I focus on the enrollment status of adolescents aged 14–19 in the baseline and their transitions to labor markets thereafter. Though our results in general conform to those in the literature, one difference is the finding of almost equal magnitudes of ex post effects of maternal and paternal deaths, partly as a result of difference in the age ranges used. Because of small incidences of parental deaths in a short period, it was not possible to estimate the ex ante effects.
Framework Specification and Estimation
This section describes our empirical methodology. The behavioral equation of interest to us is as follows:
y* ijt = α + xjtβ + γsit0 + δait0 + µij + εijt, (5.1) where, for individual i in household j at time t, our observable activity indi-
cator yijt = 1 (enrolled in school or engaged in housework) if latent variable y*
ijt ≥ 0 and yijt = 0 (in labor market) otherwise, xjt is a vector of household- level factors including the demographic composition of the household, sit0 is the highest grade completed in the initial period t0, ait0 is age at the initial period t0, µij is individual i’s fixed effect in household j, and εijt follows the standard normal cumulative distribution function (probit) or the logistic cumu-
lative distribution function (logit). As I discuss subsequently, I use conditional logit estimation to eliminate time-invariant factors in the analysis of dynamic activity transition.4
Although schooling level and age in the initial period are controlled for in equation (5.1), these time-invariant variables in addition to unobserved fixed effects do not contribute to the estimation of the transition equation. There- fore, in the estimations carried out next I include initial age and schooling fixed effects only when estimating the prime-age adult mortality effect in cross- sectional models to control for potential unobserved heterogeneity of labor supply behavior attributable to predetermined schooling attainment and age.5
4 Although multinomial logit estimation is also applicable in this context to capture participation in (1) school (adolescents) or housework (adult females), (2) the labor market, and (3) other activities, I decided to focus on (1) and (2) since the number of observations for (3) is very small in our sample of individuals in specific age ranges. The inclusion of observations for other activi-
ties destabilizes the parameter estimates in maximum likelihood estimation. 5 Including both initial schooling and age fixed effects indirectly controls for the effect of past grade repetitions on the labor supply.
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