%0 Report
        %A Jenkins, Stephen P.
%A Rios-Avila, Fernando
        %T Fitting the Bivariate Mixed Poisson Regression Model by Maximum Simulated Likelihood
        %D 2026
        %8 2026 Apr
        %I Institute of Labor Economics (IZA)
        %C Bonn
        %7 IZA Discussion Paper
        %N 18606
        %U https://www.iza.org/publications/dp18606
        %X 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.
        %K st0001
%K bimpoisson
%K bivariate mixed Poisson regression
%K maximum simulated likelihood
%K sampling function
%K count data