Pseudo Panel Data Models with Cohort Interactive Effects
When genuine panel data samples are not available, repeated cross-sectional surveys can be used to form so-called pseudo panels. In this paper, we investigate the properties of linear pseudo panel data estimators with fixed number of cohorts and time observations. We expand the setup of Inoue (2008) to models with factor residuals by adapting the approach of Ahn et al. (2013) for genuine panels. In a Monte Carlo study we find that the proposed procedure has good finite sample properties in situations with endogeneity, cohort interactive effects and near non-identification. Finally, as an illustration the proposed method is applied to data from Ecuador to study labour supply elasticity.