Estimating Individual Vulnerability to Poverty with Pseudo-Panel Data

This paper presents an original method to study individual earning dynamics using repeated cross-sectional data. Because panel data of individuals are seldom available in developing countries, it is difficult to study individual earning dynamics and related issues such as the propensity of earners to fall into poverty or vulnerability to poverty because of changes in earning. This paper shows that under the assumption that individual earning dynamics obey some basic properties and follow a simple stochastic process, the main parameters of this process can be recovered from repeated cross sectional data. The knowledge of these parameters then permits simulation of the earning dynamics of an individual, and estimate other measures of interest, such as an individual's vulnerability to poverty. The results show that model parameters recovered from pseudo-panels approximate reasonably well those estimated directly from a true panel. Moreover, implications of the model, in this case pseudo-panel measures of vulnerability to poverty, reflect closely those based on actual panel data.