 Fitting the bivariate mixed Poisson regression model by maximum simulated likelihoodStephen Jenkins and Fernando Rios-Avila () UK Stata Conference 2026 from Stata Users Group Abstract: We introduce bimpoisson, a program to fit the bivariate mixed Poisson regression model by maximum simulated likelihood using the two approaches proposed by Munkin and Trivedi (Simulated maximum likelihood estimation of multivariate mixed-Poisson regression models, with application, Econometrics Journal: 2, 29–48). By default, bimpoisson uses their sampling function approach; optionally their standard MSL approach is available. bimpoisson allows either pseudo–random uniform draws or Halton draws for simulation. Additional options allow use of antithetic acceleration and a first-order bias correction. Like Jumamyradov and Munkin (Biases in maximum simulated likelihood estimation of bivariate models, Journal of Econometric Methods: 11, 55–70), we use a modified version of Munkin and Trivedi’s sampling function to provide better coverage. We also provide postestimation tools to predict conditional count probabilities and expected counts. We examine bimpoisson’s performance using Monte Carlo simulation analysis, and our empirical illustrations fit models using the same bivariate count data as used by Xu and Hardin (Regression models for bivariate count outcomes, The Stata Journal: 16, 301–315) and Munkin and Trivedi (1999). Date: 2026-09-05 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:boc:lsug26:03 Access Statistics for this paper More papers in UK Stata Conference 2026 from Stata Users Group Contact information at EDIRC. |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.