Hausman and Taylor Estimator Analysis on The Linear Data Panel Model

Panel data modelling in the field of econometrics applies two main approaches, namely fixed effect estimators and random effects. The application of the Hausman and Taylor estimator to real data is used to test for fixed effects or random effects based on the idea that the set of estimated coefficients obtained from the fixed effect estimates is taken as a group. A good estimator is an estimator that is as close as possible to represent the characteristics of the population. The characteristics of a good estimator include unbiasedness, efficiency, and consistency. The purpose of this study is to identify the properties of the Hausman and Taylor estimator in the linear model of panel data. Based on the analysis using panel data, it is found that the Hausman and Taylor estimator on the random effects panel data is an estimator that is consistent and efficient even though it is not unbiased.