Dear all
I'm using Stata 17.1. My dataset is panel unbalanced, with N=340. Observations correspond to political parties' positions in 25 countries across different elections. My model's dependent variable is shifts (from t-1 to t) in variable Y (or dY), and I have 9 independent variables . After running xtserial, I got that my data have autocorrelation (p=0.016), so I decided to run Prais-Winsten regression, with standard errors clustered by country and election. The model contains the 9 independent variables plus 24 country dummies. The model runs smoothly (prob > F=0.000, R squared =0.119 and rho= -0.552). However, in the results for the Durbin-Watson test, I get that the value of rho(original)=1.62 is higher than the value of rho(transformed)=1.15. In all the examples I've seen of Prais-Winsten regression, the transformed value is always higher. Does this imply that the model is wrong? Do you suggest any other alternative?
Thanking you in advance
Pepe
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