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Censored Quantile Instrumental Variable Estimation with Stata

Author

Listed:
  • Victor Chernozhukov
  • Iván Fernández-Val
  • Sukjin Han
  • Amanda Kowalski

Abstract

Many applications involve a censored dependent variable and an endogenous independent variable. Chernozhukov, Fernandez-Val, and Kowalski (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 simplifes 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 & Iván Fernández-Val & Sukjin Han & Amanda Kowalski, 2018. "Censored Quantile Instrumental Variable Estimation with Stata," NBER Working Papers 24232, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:24232
    Note: AG EH TWP
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    Cited by:

    1. Young-Joo Kim & Vincent Daly, 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.
    2. 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.
    3. Männasoo, Kadri, 2022. "Working hours and gender wage differentials: Evidence from the American Working Conditions Survey," Labour Economics, Elsevier, vol. 76(C).
    4. repec:ags:aaea22:335614 is not listed on IDEAS
    5. Kushawaha, Deepak, 2025. "Understanding the role of greenfield and mergers & acquisitions foreign direct investments in renewable energy expansion in developing countries," Energy Economics, Elsevier, vol. 145(C).
    6. David M. Kaplan, 2020. "sivqr: Smoothed IV quantile regression," Working Papers 2009, Department of Economics, University of Missouri.
    7. Sanna Nivakoski, 2020. "Wealth and the effect of subjective survival probability," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(2), pages 633-670, April.
    8. Heboyan, Vahé & Hovhannisyan, Vardges & Bakhtavoryan, Rafael, 2023. "A Comprehensive Analysis of Tobacco Control Policies within a Smoothed Instrumental Variables Quantile Regression Framework," 2023 Annual Meeting, July 23-25, Washington D.C. 335614, Agricultural and Applied Economics Association.
    9. 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.
    10. Sugimoto, Kota, 2021. "Ownership versus legal unbundling of electricity transmission network: Evidence from renewable energy investment in Germany," Energy Economics, Elsevier, vol. 99(C).

    More about this item

    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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