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Distribution-free estimation of heteroskedastic binary response models in Stata

Author

Listed:
  • Jason R. Blevins

    (Ohio State University)

  • Shakeeb Khan

    (Duke University)

Abstract

In this article, we consider two recently proposed semiparametric estimators for distribution-free binary response models under a conditional median restriction. We show that these estimators can be implemented in Stata by using the nl command through simple modifications to the nonlinear least-squares probit criterion function. We then introduce dfbr, a new Stata command that implements these estimators, and provide several examples of its usage. Although it is straightforward to carry out the estimation with nl, the dfbr implementation uses Mata for improved performance and robustness. Copyright 2013 by StataCorp LP.

Suggested Citation

  • Jason R. Blevins & Shakeeb Khan, 2013. "Distribution-free estimation of heteroskedastic binary response models in Stata," Stata Journal, StataCorp LP, vol. 13(3), pages 588-602, September.
    • Handle: RePEc:tsj:stataj:v:13:y:2013:i:3:p:588-602
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    Citations

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    Cited by:

    1. T. Arduini, 2016. "Distribution Free Estimation of Spatial Autoregressive Binary Choice Panel Data Models," Working Papers wp1052, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Chen, Le-Yu & Lee, Sokbae, 2018. "Best subset binary prediction," Journal of Econometrics, Elsevier, vol. 206(1), pages 39-56.
    3. Malikov, Emir & Hartarska, Valentina, 2018. "Endogenous scope economies in microfinance institutions," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 162-182.
    4. Tiziano Arduini & Giuseppe De Arcangelis & Carlo L. Del Bello, 2012. "Balance-of-Payments Crises During the Great Recession: Is This Time Different?," Review of International Economics, Wiley Blackwell, vol. 20(3), pages 517-534, August.
    5. Chen, Songnian & Khan, Shakeeb & Tang, Xun, 2016. "Informational content of special regressors in heteroskedastic binary response models," Journal of Econometrics, Elsevier, vol. 193(1), pages 162-182.
    6. Edoardo Rainone, 2017. "Pairwise trading in the money market during the European sovereign debt crisis," Temi di discussione (Economic working papers) 1160, Bank of Italy, Economic Research and International Relations Area.
    7. Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    8. Difang Huang & Jiti Gao & Tatsushi Oka, 2022. "Semiparametric Single-Index Estimation for Average Treatment Effects," Papers 2206.08503, arXiv.org, revised Apr 2024.
    9. Carlson, Alyssa, 2023. "Relaxing conditional independence in an endogenous binary response model," Journal of Econometrics, Elsevier, vol. 232(2), pages 490-500.
    10. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    11. Tiziano Arduini & Giuseppe De Arcangelis & Carlo L. Del Bello, 2011. "Currency Crises During the Great Recession: Is This Time Different?," Working Papers 1/11, Sapienza University of Rome, DISS.
    12. Henry R. Scharf & Xinyi Lu & Perry J. Williams & Mevin B. Hooten, 2022. "Constructing Flexible, Identifiable and Interpretable Statistical Models for Binary Data," International Statistical Review, International Statistical Institute, vol. 90(2), pages 328-345, August.
    13. Satimanon, Monthien & Lupi, Frank, 2010. "Comparison of Approaches to Estimating Demand for Payment for Environmental Services," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61288, Agricultural and Applied Economics Association.
    14. David Powell, 2020. "Quantile Treatment Effects in the Presence of Covariates," The Review of Economics and Statistics, MIT Press, vol. 102(5), pages 994-1005, December.
    15. Ahmad, Munir & Wu, Yiyun, 2022. "Household-based factors affecting uptake of biogas plants in Bangladesh: Implications for sustainable development," Renewable Energy, Elsevier, vol. 194(C), pages 858-867.

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