7. Fixed-Effects Negative Binomial Regression Models
California University of Pennsylvania · University of Pennsylvania
Abstract
This paper demonstrates that the conditional negative binomial model for panel data, proposed by Hausman, Hall, and Griliches (1984), is not a true fixed-effects method. This method—which has been implemented in both Stata and LIMDEP—does not in fact control for all stable covariates. Three alternative methods are explored. A negative multinomial model yields the same estimator as the conditional Poisson estimator and hence does not provide any additional leverage for dealing with over-dispersion. On the other hand, a simulation study yields good results from applying an unconditional negative binomial regression estimator with dummy variables to represent the fixed effects. There is no evidence for any…
Citation impact
- FWCI
- 15.96
- Percentile
- 100%
- References
- 18
Authors
2Topics & keywords
- Negative binomial distribution
- Estimator
- Statistics
- Mathematics
- Econometrics
- Count data
- Fixed effects model
- Covariate