Thank you for providing the requested information. I'm sorry to keep pestering you, but I greatly appreciate the help! I'm switching back to SAS from MATLAB, and I want to make sure my code is giving me what I want it to. When it comes to fixed and random effects models (fixed time effects, fixed country effects, random time effects, and random country effects), when is it okay to have the Country variable coded as the country name, and when must it be coded as an integer? (sort by Country and then Year) then I am going to be estimating a one-way random effects model on Country, correct? As far as I know, if I sort by Country and then Year, there is no "ranonetime" option or something similar that is analogous to the "fixonetime" option when doing fixed effects.Īre you saying that the Country variable(or whatever cross-section variable is being used) always needs to be an integer anytime a random effects model with respect to Year(or whatever time-series variable is being used) is run? Is this also true for a fixed effects model on time?Īnother way, and perhaps a better way, to ask my question is this. If the code above (with Country NOT an integer) is wrong, I'm not sure what to do.
Is not telling SAS to run a one-way random effects model on time? Or am I correctly coding for such a model, and you are just saying that because Country is not an integer, the hausman m-statistic is going to be inaccurate? My country variable is currently not defined as an integer. The Electricity data set can be found in the following link: The Electricity data set in the Getting Started section of the PROC PANEL documentation is an example of a data set where this approach would be acceptable, since the cross-section variable, FIRM, takes on the values 1 thru 6. In other words, if the levels of COUNTRY are defined as integer values, then it should be fine. Is an acceptable approach, as long as your COUNTRY variable is coded in such a way that it can be inferred as a time variable. Regarding your question on fitting a one-way random effects model on time and computing Hausman's test, R&D indicated that your original specification (without the HCCME= option): I'm glad that removing the HCCME= option allowed you to obtain the Hausman m-statistic.
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