Panel Data Analysis Using GAUSS 3 Kuan-Pin Lin Portland State University

Random Effects Model Estimation: GLS The Model

Random Effects Model Estimation: GLS GLS

Random Effects Model Estimation: GLS Feasible GLS Based on estimated residuals of fixed effects model

Random Effects Model Estimation: GLS Feasible GLS Within Model Representation

Model Estimation: RE-GLS Partial Group Mean Deviations

Model Estimation: RE-GLS Model Assumptions OLS

Model Estimation: RE-GLS Need a consistent estimator of  : Estimate the fixed effects model to obtain Estimate the between model to obtain Or, estimate the pooled model to obtain Based on the estimated large sample variances, it is safe to obtain

Model Estimation: RE-OLS Panel-Robust Variance-Covariance Matrix Consistent statistical inference for general heteroscedasticity, time series and cross section correlation.

Random Effects Model Estimation: ML Log-Likelihood Function

Random Effects Model Estimation: ML where

Random Effects Model Estimation: ML ML Estimator

Random Effects Model Hypothesis Testing Pool or Not Pool Test for Var(u i ) = 0, that is For balanced panel data, the Lagrange-multiplier test statistic (Breusch-Pagan, 1980) is:

Random Effects Model Hypothesis Testing Pool or Not Pool (Cont.)

References B. H. Baltagi, Econometric Analysis of Panel Data, 4th ed., John Wiley, New York, W. H. Greene, Econometric Analysis, 7th ed., Chapter 11: Models for Panel Data, Prentice Hall, C. Hsiao, Analysis of Panel Data, 2nd ed., Cambridge University Press, J. M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, The MIT Press, 2002.