The Hausman test in Panel Data Analysis by using STATA

Full text: https://phantran.net/the-hausman-test...
Database: https://drive.google.com/file/d/1G3NF...
Data in excel: https://docs.google.com/spreadsheets/...

The Durbin–Wu–Hausman test (also called Hausman specification test) is a statistical hypothesis test in econometrics named after James Durbin, De-Min Wu, and Jerry A. Hausman. The test evaluates the consistency of an estimator when compared to an alternative, less efficient estimator which is already known to be consistent. It helps one evaluate if a statistical model corresponds to the data.

It is also applied in the context of linear regression to decide whether to choose a fixed effect model or a random effect model.

The null hypothesis for Hausman’s test, in this case, is that we use the random-effects model because it is more efficient. On the other hand, the alternative hypothesis tells us that we should use the fixed effects model since the random effect model is not consistent.

The hypotheses:
H0: Random-effects (RE) is preferred
H1: Fixed-effects (FE) is preferred
By applying the procedure for Hausman’s test given above we can decide which model (Fixed Effects vs Random Effects) is better. We can also apply Hausman’s test to check for the endogeneity of variables in a regression model.