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http://hdl.handle.net/2451/26184
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| Title: | The Behavior of the Fixed Effects Estimator in Nonlinear Models, |
| Authors: | Greene, William |
| Keywords: | Panel data
fixed effects
computation
Monte Carlo |
| Issue Date: | Feb-2002 |
| Series/Report no.: | EC-02-05 |
| Abstract: | The nonlinear fixed effects models in econometrics has often been
avoided for two reasons one practical, one methodological. The practical
obstacle relates to the difficulty of estimating nonlinear models with
possibly thousands of coefficients. In fact, in a large number of models
of interest to practitioners, estimation of the fixed effects model is
feasible even in panels with very large numbers of groups. The more
difficult, methodological question centers on the incidental parameters
problem that raises questions about the statistical properties of the
estimator. There is very little empirical evidence on the behavior of
the fixed effects estimator. In this note, we use Monte Carlo methods to
examine the small sample bias in the binary probit and logit models, the
ordered probit model, the tobit model, the Poisson regression model for
count data and the exponential regression model for a nonnegative random
variable. We find three results of note: A widely accepted result that
suggests that the probit estimator is actually relatively well behaved
appears to be incorrect. Perhaps to some surprise, the tobit model,
unlike the others, appears largely to be unaffected by the incidental
parameters problem, save for a surprising result related to the
disturbance variance estimator. Third, as apparently unexamined
previously, the estimated asymptotic estimators for fixed effects
estimators appear uniformly to be downward biased. |
| URI: | http://hdl.handle.net/2451/26184 |
| Appears in Collections: | Economics Working Papers
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