Estimation of AR(1) models with unequally spaced pseudo-panels

Surveys in developing countries are often taken at unequally spaced intervals. This paper provides for the estimation of dynamic pseudo-panel models with such data. Non-linear least squares, minimum distance, and one-step estimators are used to impose the non-linear parameter restrictions which occur in dynamic models over unequally spaced periods. Consistency and asymptotic normality of the estimators is established. A small-scale Monte Carlo simulation study corroborates the results. The paper also shows how these methods can be applied to allow estimation of dynamic models with irregularly spaced genuine panel data.