4.4. Fixed Effects Negative Binomial Models for Count Data

As we just saw in the last section, Poisson regression models often run into problems with overdispersion. That's a bit surprising for fixed effects models because these models already allow for unobserved heterogeneity across individuals by way of the αi parameters. But that heterogeneity is presumed to be time-invariant. There might still be unobserved heterogeneity that is specific to particular points in time, leading to observed overdispersion. As we've seen, the standard errors can be corrected for overdispersion by a simple method based on the ratio of the deviance (or Pearson chi-square) to its degrees of freedom.

Although that's not a bad method, we might do better by directly ...

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