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Maximum simulated likelihood estimation of a negative binomial regression model with multinomial endogenous treatment

Author

Listed:
  • Partha Deb

    (Hunter College, City University of New York)

  • Pravin K. Trivedi

    (Indiana University)

Abstract

We describe specification and estimation of a multinomial treatment effects negative binomial regression model. A latent factor structure is used to accommodate selection into treatment, and a simulated likelihood method is used for estimation. We describe its implementation via the mtreatnb command. Copyright 2006 by StataCorp LP.

Suggested Citation

  • Partha Deb & Pravin K. Trivedi, 2006. "Maximum simulated likelihood estimation of a negative binomial regression model with multinomial endogenous treatment," Stata Journal, StataCorp LP, vol. 6(2), pages 246-255, June.
    • Handle: RePEc:tsj:stataj:v:6:y:2006:i:2:p:246-255
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    References listed on IDEAS

    as
    1. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    2. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    4. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
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