Hausman test negative result

[Tiffany Volken]

Hi everyone,

I am doing a panel data approach that has data for female regular and non regular employment and male regular and non regular employment data for each prefecture over time in 5 year intervals. I am seeing how the lost decade has caused a change in male regular work and what effect that has had on female non regular employment.

I started off by doing a pooled OLS estimator first and wrote down the equation and analysed by saying there unobserved prefecture specific characteristics and then added an individual heterogeneity term to get the individual effects model. Then I decide whether I should use REM or FEM and use the hausman test to see which is better. I then get the results chi2 (3) = -219.03; Prob>chi2 = 0.0000 and a message from state saying model fails to meet the asymptotic assumptions of the Hausman test.

I then proceed to run the F test to see if the FEM should be used over the pooled OLS and get [F(46, 3717) = 45.16; Prob > F = 0.000]

is this enough to say I am going to use the FEM model or should I use the Breusch Pagan LM test to see for REM?

I also have to think about the lost decade and how this has shaped.

I'm just confused as I cant use the hausman test and don't really know if this is because of my data or stats commands?

[Andrew Musau]

The fixed effects (FE) estimator is consistent regardless of whether the random effects (RE) assumption holds. By contrast, the RE estimator is only consistent in the absence of correlation between the unobserved effects and the regressors. Thus, the Hausman test is typically used to assess whether the RE assumptions are valid and thus to justify the use of RE over FE. In summary, one simply estimates the FE model to ensure consistency and avoid relying on specification tests, although this may come at the cost of efficiency if the RE assumptions do in fact hold.