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Estimation of Nested and Zero-Inflated Ordered Probit Models

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Listed:
  • David Dale

    (Yandex)

  • Andrei Sirchenko

    (National Research University Higher School of Economics)

Abstract

We introduce three new STATA commands, nop, ziop2 and ziop3, for the estimation of a three-part nested ordered probit model, the two-part zero-inflated ordered probit models of Harris and Zhao (2007, Journal of Econometrics 141: 1073-1099) and Brooks, Harris and Spencer (2012, Economics Letters 117: 683-686), and a three-part zero-inflated ordered probit model for ordinal outcomes, with both exogenous and endogenous switching. The three-part models allow the probabilities of positive, neutral (zero) and negative outcomes to be generated by distinct processes. The zero-inflated models address a preponderance of zeros and allow them to emerge in different latent regimes. We provide postestimation commands to compute probabilistic predictions and various measures of their accuracy, to access the goodness of fit, and to perform model comparison using the Vuong test (Vuong 1989, Econometrica 57: 307-333) with the corrections based on the Akaike and Schwarz information criteria. We investigate the finite-sample performance of the maximum likelihood estimators by Monte Carlo simulations, discuss the relations among the models, and illustrate the new commands with an empirical application to the U.S. federal funds rate target.

Suggested Citation

  • David Dale & Andrei Sirchenko, 2018. "Estimation of Nested and Zero-Inflated Ordered Probit Models," HSE Working papers WP BRP 193/EC/2018, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:193/ec/2018
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    References listed on IDEAS

    as
    1. Small, Kenneth A, 1987. "A Discrete Choice Model for Ordered Alternatives," Econometrica, Econometric Society, vol. 55(2), pages 409-424, March.
    2. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    3. Bagozzi, Benjamin E. & Mukherjee, Bumba, 2012. "A Mixture Model for Middle Category Inflation in Ordered Survey Responses," Political Analysis, Cambridge University Press, vol. 20(3), pages 369-386, July.
    4. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    5. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    6. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    7. Wilson, Paul, 2015. "The misuse of the Vuong test for non-nested models to test for zero-inflation," Economics Letters, Elsevier, vol. 127(C), pages 51-53.
    8. Sirchenko Andrei, 2012. "A model for ordinal responses with an application to policy interest rate," EERC Working Paper Series 12/13e, EERC Research Network, Russia and CIS.
    9. James W. Hardin & Joseph M. Hilbe, 2014. "Estimation and testing of binomial and beta-binomial regression models with and without zero inflation," Stata Journal, StataCorp LP, vol. 14(2), pages 292-303, June.
    10. Brooks, Robert & Harris, Mark N. & Spencer, Christopher, 2012. "Inflated ordered outcomes," Economics Letters, Elsevier, vol. 117(3), pages 683-686.
    11. Harris, Mark N. & Zhao, Xueyan, 2007. "A zero-inflated ordered probit model, with an application to modelling tobacco consumption," Journal of Econometrics, Elsevier, vol. 141(2), pages 1073-1099, December.
    12. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, September.
    13. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521142373.
    14. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
    15. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204.
    16. William H. Greene, 1994. "Accounting for Excess Zeros and Sample Selection in Poisson and Negative Binomial Regression Models," Working Papers 94-10, New York University, Leonard N. Stern School of Business, Department of Economics.
    17. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    18. Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
    19. Basu Deepankar & de Jong Robert M, 2007. "Dynamic Multinomial Ordered Choice with an Application to the Estimation of Monetary Policy Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(4), pages 1-35, December.
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    Cited by:

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    2. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.

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    More about this item

    Keywords

    ordinal outcomes; zero inflation; nested ordered probit; zero-inflated ordered probit; endogenous switching; Vuong test; nop; ziop2; ziop3; federal funds rate target.;
    All these keywords.

    JEL classification:

    • Z - Other Special Topics

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