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From | "Santos Silva, J.M.C." <jmcss@essex.ac.uk> |
To | <statalist@hsphsun2.harvard.edu> |
Subject | RE: st: Count models and fractional variables |
Date | Sat, 17 Mar 2012 16:02:14 GMT |
Dear Fabiana, Sorry for not seeing you post earlier. Let me see if I can clarify this. First, your friend should not use the Tobit as it is meant for truncated data and there is no truncation in this dataset. Second, the ZI models can be estimated even if the dependent variable is continuous. So, there is no need to round the data and of course you get different results if you do. The fact that you can estimate zero inflated models with continuous data does not mean that it is a good idea to do it! In particular, the results of zero inflated models are not invariant to the scale of the dependent variable, and that explains why different results are obtained if it is multiplied by 10000. The reason for this is that by rescaling the variable you change the amount of overdispersion (the mean is multiplied by k and the variance by k^2). Therefore, studying the number of patents per year of by quarter will give different results! The advice is now obvious: go back to modeling the counts using an appropriate count data model (is zero inflation really needed?). In general, my advice is that one should model the variable we care about and not some transformation of it; as this example illustrates, messing with the dependent variable may have very undesirable consequences. All the best, Joao * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/