Hello together,
I am regressing a panel data model with t=12 and n=230. In general, I measure the effect of public finance on private finance regarding solar module investments for 38 countries in total. My model consits of Heteroscedasticity, as I found out using the Modified Wald test ( Result: Prob>chi2 = 0.0000)
Now I want to know whether I should use Fixed or Random Effects for my regriession model. I conduct the Hausman-Test (see screenshot below). It gives me a test-statistic of Prob>chi2 = 0.9235 , meaning the hypothesis can not be rejected so I should go for Random effects.
Q1) From what I understood, Random effects reduces the effect of the "within" estimation. In my opinion, this might be counterproductive, as I want to test the impact of public finance on private finance in each country over time. To me, this rather implies FE, but Hausman Test does not validate this. Using RE would disagree and put more focus on comparing effects "between", meaning accross countries. Can I just use FE, even though Hausmann Test provides different result?
Q2) If yes, how could I argue for my arbitrary approach, contradicting Hausman Test?
Q3) Could it be, that the dummies (and interactions containing dummies), lead to Hausmanns suggestion in using RE? As the marked variables (1)-(4) contain dummies in form of "gdp_cluster_group", I am depending on these to be integrated into my model.
Thank you in advance!Array
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