Short Guides to Static Panel Data Regression Model Estimator

Abstract

This paper elaborates on the use of three regression model estimators under the classification of static panel data. In order to select the best regression model estimator for panel data analysis, the researcher should focus on conducting several tests to avoid bias in the estimation results. The Breusch Pagan Lagrangian Multiplier test (Breusch Pagan test) is a simple test carried out in the panel data analysis to check for heteroscedastic disturbances in the linear regression model in making the decision to choose whether Pooled Ordinary Least Square or Random Effects. If the Breusch Pagan test shows the rejection of the null hypothesis, it indicates that the Random Effect model is more appropriate than Pooled Ordinary Least Square because the data have a panel effect (unobserved heterogeneity). The panel effect should be checked using the Hausman test in order to identify whether the effects are correlated or uncorrelated with the regressors. In the case of rejection of the null hypothesis, the Fixed Effect estimator is a more appropriate or unbiased estimator to analyze the data.