Which r2 is considered in random effect model of panel regression?
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Answer:
Step-by-step explanation:
Dear Urvi,
I do agree with the opinion of Prof. James R Knaub that R square is not very informative in this case. In panel data analysis, rely more on individual significance and overall significance of the model instead of R square or adjusted R square. Generally, R square is low in cross sectional data as compared to time series data. In panel data due to heterogeneity of cross sections, it is not too high. If your data is more time dominant, R square can be higher as compared to the case when panel data is more cross section dominant. In general, more related included explanatory variables boost the value of R square. Yet, one has to focus more on objectives of the research to be fulfilled from individual significance and overall significance of the model making sure that there is no model specification bias and avoid spurious regressions. Another point to mention here is that a very high R square in the presence of very few significant t values indicates the presence of multicollinearity and spuriousness of the regression.
Best wishes,