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From |
"Scott Merryman" <smerryman@kc.rr.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Re: Negative binomial regression question |

Date |
Tue, 17 Feb 2004 19:24:21 -0600 |

Ed, Paul Allison has argued that it is acceptable to estimate a unconditional fixed-effects model and correct the standard errors. See "Fixed-Effects Negative Binomial Regression Models" (http://www.ssc.upenn.edu/~allison/FENB.pdf) "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 overdispersion. 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 incidental parameters bias in the coefficients, and downward bias in the standard error estimates can be easily and effectively corrected using the deviance statistic. Finally, an approximate conditional method is found to perform at about the same level as the unconditional estimator." Also, it may be sufficient to account for the unobserved heterogeneity using a unconditional fixed-effects Poisson model. At least for the Poisson fixed effects model, there is no incidental parameter problem (see Cameron and Trivedi, "Regression Analysis of Count Data" page 280-282). Scott ----- Original Message ----- From: "Ed Levitas" <levitas@uwm.edu> To: <statalist@hsphsun2.harvard.edu> Sent: Monday, February 09, 2004 1:30 PM Subject: st: Negative binomial regression question > Statalisters, > > I have a question regarding a negative binomial regression model I want to > estimate with panel data. I would like to estimate a conditional fixed > effects model with robust standard errors. XTNBREG does not allow this > option (perhaps this does not make "statistical sense"). Is there a way to > estimate such a model with GNBREG (e.g., using GBGREG I've tried to include > cross-section specific fixed effects in the estimation of the dispersion > parameter via the LN(ALPHA) command. However, I don't seem to achieve > convergence doing this.) > > Any suggestions would be greatly appreciated. > > Thanks > Ed > > > > **************************************** > Edward Levitas, PhD > Assistant Professor > School of Business Administration > University of Wisconsin-Milwaukee > 3202 N. Maryland Ave. > Milwaukee, WI 53211 > ph: (414) 229-6825 > fx: (414) 229-6957 > levitas@uwm.edu > * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Negative binomial regression question***From:*Ed Levitas <levitas@uwm.edu>

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