# What is the best technique for panel regressions (ols, fixed, between, random effects)?

I have panel data which includes American states (1-48) and years (1900-1917). All the variables are time-varying with one exception. This exception is time invariant and a three level categorical variable measuring regional designations for the states tested using two dummy variables. I also want look at interactions between one of the dummies and several of the time-varying variables. OLS estimates of this model indicate heteroscedasticity. So given the organization of the data my question is which of the panel techniques is best and why? I am using Stata. Thanks, RB

• OLS vs. Fixed effects: F-test of the joint significance of the fixed effects intercepts. The null hypothesis is that all of the fixed effect intercepts are zero. If the null is rejected, then we need to use fixed effects method. The F-test is automatically conducted when we run xtreg in Stata. It appears at the bottom of regression output.
• Fixed vs. random effects: Hausman test. The null hypothesis is that the slope coefficients of the two models being compared do not differ significantly. If the estimates are different then we reject romdom effects and must use fixed effects, otherwise we use the more efficient random effects method. There is a command hausman in Stata.