Fitting the Bivariate Mixed Poisson Regression Model by Maximum Simulated Likelihood

Stephen Jenkins () and Fernando Rios-Avila ()
Additional contact information
Stephen Jenkins: London School of Economics
Fernando Rios-Avila: London School of Economics

No 18606, IZA Discussion Papers from IZA Network @ LISER

Abstract: We introduce bimpoisson, a program to fit the bivariate mixed Poisson regression model by maximum simulated likelihood (MSL) as per Munkin and Trivedi (The Econometrics Journal, 1999). Options include: sampling function or standard MSL; pseudo-random uniform or Halton draws, antithetic acceleration, and a first-order bias correction. We also provide post-estimation tools to predict conditional count probabilities and expected counts. We examine bimpoisson’s performance using Monte Carlo simulation analysis and provide two empirical illustrations using data from Xu and Hardin (The Stata Journal, 2016) and Munkin and Trivedi (1999). We provide practical advice about which MSL estimator and types of draws and number to use.

Keywords: st0001; bimpoisson; bivariate mixed Poisson regression; maximum simulated likelihood; sampling function; count data (search for similar items in EconPapers)
JEL-codes: C15 C31 C35 (search for similar items in EconPapers)
Date: 2026-04
References: Add references at CitEc
Citations:

Downloads: (external link)
https://docs.iza.org/dp18606.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp18606

Access Statistics for this paper

More papers in IZA Discussion Papers from IZA Network @ LISER Contact information at EDIRC.
Bibliographic data for series maintained by Mark Fallak ().