I'm in a bit of a pinch here. I am working on my undergrad capstone project, examining the relationship between income inequality and violent crime in U.S. counties. Here is my dilemma: I believe my dependent variable (number of violent crimes) to be count data, correct? It is a simple count of how many times a violent crime occured in county X. I have been advised that this is not the case, however, I have a strong feeling that I am correct on this. A number of previous studies on the subject have utilized either a poisson regression or a negative binomial regression model while exploring essentially the same topic. I am referencing Morgan Kelly (2000) inequality and crime as my guide through this paper. I feel as though negative binomial regression is the way to go, however I have been advised to use a tobit model. Any suggestions?
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