Hello all,
I am performing linear regression on panel data using a LSDV estimator. The regression command takes the form of something like: reg y x1-x12 i.firm i.year i.country, robust ... Everything is progressing as hoped, but I wanted to run an additional robustness check on the data and I include country by year dummies (i.e., i.country##i.year). The results come back as hoped in terms of direction of certain coefficients and their corresponding t values, but the overall model F stat is blank. From reading, I understand this is likely because there are so many predictors in the model. My question is ... can I safely interpret this auxiliary model as supporting my other primary results and correspondingly say in my paper that the results of this additional test further supports my hypotheses? or... is the model invalid since the model F statistic is blank?
Thanks!
I am performing linear regression on panel data using a LSDV estimator. The regression command takes the form of something like: reg y x1-x12 i.firm i.year i.country, robust ... Everything is progressing as hoped, but I wanted to run an additional robustness check on the data and I include country by year dummies (i.e., i.country##i.year). The results come back as hoped in terms of direction of certain coefficients and their corresponding t values, but the overall model F stat is blank. From reading, I understand this is likely because there are so many predictors in the model. My question is ... can I safely interpret this auxiliary model as supporting my other primary results and correspondingly say in my paper that the results of this additional test further supports my hypotheses? or... is the model invalid since the model F statistic is blank?
Thanks!
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