IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v21y2021i1p3-38.html
   My bibliography  Save this article

Estimation of nested and zero-inflated ordered probit models

Author

Listed:
  • David Dale
  • Andrei Sirchenko

    (University of Amsterdam)

Abstract

We introduce three new 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 of Sirchenko (2020, Studies in Nonlinear Dynamics and Econometrics 24: 1) 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 assess 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, 2021. "Estimation of nested and zero-inflated ordered probit models," Stata Journal, StataCorp LP, vol. 21(1), pages 3-38, March.
    • Handle: RePEc:tsj:stataj:v:21:y:2021:i:1:p:3-38
    DOI: 10.1177/1536867X211000002
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj21-1/st0625/
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1177/1536867X211000002
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1536867X211000002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    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. 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.
    4. 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.
    5. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    6. 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.
    7. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    8. 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.
    9. 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.
    10. Brooks, Robert & Harris, Mark N. & Spencer, Christopher, 2012. "Inflated ordered outcomes," Economics Letters, Elsevier, vol. 117(3), pages 683-686.
    11. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204.
    12. 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.
    13. 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.
    14. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, January.
    15. 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.
    16. 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.
    17. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    2. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Benjamin E. Bagozzi, 2016. "The baseline-inflated multinomial logit model for international relations research," Conflict Management and Peace Science, Peace Science Society (International), vol. 33(2), pages 174-197, April.
    3. Sarah Brown & Mark N. Harris & Christopher Spencer, 2020. "Modelling Category Inflation with Multiple Inflation Processes: Estimation, Specification and Testing," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(6), pages 1342-1361, December.
    4. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.
    5. Craig W. Carpenter & Anders Van Sandt & Rebekka Dudensing & Scott Loveridge, 2022. "Profit Pools and Determinants of Potential County-Level Manufacturing Growth," International Regional Science Review, , vol. 45(2), pages 188-224, March.
    6. Andrei Sirchenko, 2019. "A regime-switching model for the federal funds rate target," UvA-Econometrics Working Papers 19-01, Universiteit van Amsterdam, Dept. of Econometrics.
    7. William H Greene & Mark N Harris & Preety Srivastava & Xueyan Zhao, 2013. "Econometric Modelling of Social Bads," Bankwest Curtin Economics Centre Working Paper series WP1305, Bankwest Curtin Economics Centre (BCEC), Curtin Business School.
    8. Belderbos, Rene & Ikeuchi, Kenta & Fukao, Kyoji & Kim, Young Gak & Kwon, Hyeog Ug, 2013. "Plant Productivity Dynamics and Private and Public R&D Spillovers: Technological, Geographic and Relational Proximity," CEI Working Paper Series 2013-05, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    9. Entorf, Horst, 2013. "Criminal Victims, Victimized Criminals, or Both? A Deeper Look at the Victim-Offender Overlap," IZA Discussion Papers 7686, Institute of Labor Economics (IZA).
    10. William Greene & Mark N. Harris & Preety Srivastava & Xueyan Zhao, 2018. "Misreporting and econometric modelling of zeros in survey data on social bads: An application to cannabis consumption," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 372-389, February.
    11. Greene, William & Harris, Mark N. & Knott, Rachel & Rice, Nigel, 2023. "Reporting heterogeneity in modeling self-assessed survey outcomes," Economic Modelling, Elsevier, vol. 124(C).
    12. David ARISTEI & Manuela Gallo, 2012. "The Drivers of Household Over-Indebtedness and Delinquency on Mortgage Loans: Evidence from Italian Microdata," Quaderni del Dipartimento di Economia, Finanza e Statistica 105/2012, Università di Perugia, Dipartimento Economia.
    13. Tianji Cai & Yiwei Xia & Yisu Zhou, 2021. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," Sociological Methods & Research, , vol. 50(1), pages 365-400, February.
    14. Cai, Tianji & Xia, Yiwei & Zhou, Yisu, 2017. "Generalized Inflated Discrete Models: A Strategy to Work with Multimodal Discrete Distributions," SocArXiv 4r2j3, Center for Open Science.
    15. William Greene, 2009. "Models for count data with endogenous participation," Empirical Economics, Springer, vol. 36(1), pages 133-173, February.
    16. William H.Greene & Max Gillman & Mark N. Harris & Christopher Spencer, 2013. "The Tempered Ordered Probit (TOP) model with an application to monetary policy," Discussion Paper Series 2013_10, Department of Economics, Loughborough University, revised Sep 2013.
    17. Makram El‐Shagi & Gregor von Schweinitz, 2022. "Why they keep missing: An empirical investigation of sovereign bond ratings and their timing," Scottish Journal of Political Economy, Scottish Economic Society, vol. 69(2), pages 186-224, May.
    18. Llerena, Freddy, 2012. "Determinantes de la fecundidad en el Ecuador [Determinants of fertility in Ecuador]," MPRA Paper 39887, University Library of Munich, Germany, revised Feb 2012.
    19. Fumagalli, Elena & Fumagalli, Laura, 2022. "Subjective well-being and the gender composition of the reference group: Evidence from a survey experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 196-219.
    20. Elbakidze, Levan & Beeson, Quinn, 2020. "State Regulatory Heterogeneity and Clean Water Act Compliance," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304638, Agricultural and Applied Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tsj:stataj:v:21:y:2021:i:1:p:3-38. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.