Monte Carlo analysis for dynamic panel data models

The Monte Carlo strategy by McLeod and Hipel (Water Resources Research, 1978), originally thought for time series data, has been adapted to dynamic panel data models by Kiviet (1995). This procedure is more efficient than the traditional approaches in that it generates start-up values according to the data generation process, so it avoids wasting random numbers in the generation of initial conditions and also small sample non-stationarity problems. This presentation discusses my Stata implementation of Kiviet's (Journal of Econometrics, 1995) procedure, as used in Bruno (2005) and (2004) to evaluate the finite sample properties of theoretical approximations for the LSDV bias (Bruno (Economics Letters 2005; UKSUG 2004)) and of the bias-corrected LSDV estimator (Bruno (2004); Italian SUG 2004) in the presence of unbalanced designs.