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Censored Quantile Instrumental Variable Estimation with Stata

Author

Listed:
  • Victor Chernozhukov

    (MIT)

  • Iv'n Fern'ndez-Val

    (Boston University)

  • Sukjin Han

    (UT Austin)

  • Amanda E. Kowalski

    (Cowles Foundation, Yale University)

Abstract

Many applications involve a censored dependent variable and an endogenous independent variable. Chernozhukov et al. (2015) introduced a censored quantile instrumental variable estimator (CQIV) for use in those applications, which has been applied by Kowalski (2016), among others. In this article, we introduce a Stata command, cqiv, that simplifies application of the CQIV estimator in Stata. We summarize the CQIV estimator and algorithm, we describe the use of the cqiv command, and we provide empirical examples.

Suggested Citation

  • Victor Chernozhukov & Iv'n Fern'ndez-Val & Sukjin Han & Amanda E. Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," Cowles Foundation Discussion Papers 2120, Cowles Foundation for Research in Economics, Yale University.
    • Handle: RePEc:cwl:cwldpp:2120
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2120.pdf
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    References listed on IDEAS

    as
    1. Chernozhukov, Victor & Fernández-Val, Iván & Kowalski, Amanda E., 2015. "Quantile regression with censoring and endogeneity," Journal of Econometrics, Elsevier, vol. 186(1), pages 201-221.
    2. Victor Chernozhukov & Iv·n Fern·ndez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves Without Crossing," Econometrica, Econometric Society, vol. 78(3), pages 1093-1125, May.
    3. repec:hal:wpspec:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
    4. Powell, James L., 1986. "Censored regression quantiles," Journal of Econometrics, Elsevier, vol. 32(1), pages 143-155, June.
    5. repec:hal:spmain:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
    6. Amanda Kowalski, 2016. "Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 107-117, January.
    7. Foresi, S. & Paracchi, F., 1992. "The Conditional Distribution of Excess Returns: An Empirical Analysis," Working Papers 92-49, C.V. Starr Center for Applied Economics, New York University.
    8. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    9. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

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    2. Kim, Young-Joo & Daly, Vincent, 2019. "The Education Gradient in Health: The Case of Obesity in the UK and US," Economics Discussion Papers 2019-4, School of Economics, Kingston University London.
    3. L. Benfratello & A. Bottasso & C. Piccardo, 2022. "R&D and export performance: exploring heterogeneity along the export intensity distribution," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(2), pages 189-232, June.
    4. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    5. repec:ags:aaea22:335614 is not listed on IDEAS
    6. Dunn, Abe, 2016. "Health insurance and the demand for medical care: Instrumental variable estimates using health insurer claims data," Journal of Health Economics, Elsevier, vol. 48(C), pages 74-88.
    7. Sugimoto, Kota, 2021. "Ownership versus legal unbundling of electricity transmission network: Evidence from renewable energy investment in Germany," Energy Economics, Elsevier, vol. 99(C).
    8. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.

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    More about this item

    Keywords

    st0001; cqiv; quantile regression; censored data; endogeneity; instrumental variable; control function;
    All these keywords.

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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