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Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods

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  • Callaway, Brantly
  • Li, Tong
  • Oka, Tatsushi

Abstract

This paper shows that the Conditional Quantile Treatment Effect on the Treated is identified under (i) a Conditional Distributional Difference in Differences assumption and (ii) a new assumption that the dependence (the copula) between the change in untreated potential outcomes and the initial level of untreated potential outcomes is the same for the treated group and untreated group. We consider estimation and inference with discrete covariates and propose a uniform inference procedure based on the exchangeable bootstrap. Finally, we estimate the effect of increasing the minimum wage on the distribution of earnings for subgroups defined by race, gender, and education.

Suggested Citation

  • Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
  • Handle: RePEc:eee:econom:v:206:y:2018:i:2:p:395-413
    DOI: 10.1016/j.jeconom.2018.06.008
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    Cited by:

    1. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    2. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    3. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    4. Jessica Ya Sun, 2020. "Welfare consequences of access to health insurance for rural households: Evidence from the New Cooperative Medical Scheme in China," Health Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 337-352, March.
    5. David Bounie & Youssouf Camara, 2020. "Card-Sales Response to Merchant Contactless Payment Acceptance," Post-Print hal-02296302, HAL.
    6. Peng, Ying & Tian, Chuanhao & Wen, Haizhen, 2021. "How does school district adjustment affect housing prices: An empirical investigation from Hangzhou, China," China Economic Review, Elsevier, vol. 69(C).
    7. Afrouz Azadikhah Jahromi & Brantly Callaway, 2022. "Heterogeneous Effects of Job Displacement on Earnings," Empirical Economics, Springer, vol. 62(1), pages 213-245, January.
    8. Bounie, David & Camara, Youssouf, 2020. "Card-sales response to merchant contactless payment acceptance," Journal of Banking & Finance, Elsevier, vol. 119(C).
    9. Pedro H. C. Sant'Anna, 2016. "Program Evaluation with Right-Censored Data," Papers 1604.02642, arXiv.org.
    10. Jiafeng Gu, 2021. "Effects of Patent Policy on Outputs and Commercialization of Academic Patents in China: A Spatial Difference-in-Differences Analysis," Sustainability, MDPI, vol. 13(23), pages 1-17, December.
    11. Saibal Ghosh, 2020. "Bank Lending and Monetary Transmission: Does Politics Matter?," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(2), pages 359-381, June.
    12. Soichiro Yamauchi, 2020. "Difference-in-Differences for Ordinal Outcomes: Application to the Effect of Mass Shootings on Attitudes toward Gun Control," Papers 2009.13404, arXiv.org.
    13. Goodman-Bacon, Andrew, 2021. "Difference-in-differences with variation in treatment timing," Journal of Econometrics, Elsevier, vol. 225(2), pages 254-277.
    14. Masayuki Sawada, 2019. "Noncompliance in randomized control trials without exclusion restrictions," Papers 1910.03204, arXiv.org, revised Jun 2021.
    15. David Bounie & Youssouf Camara, 2019. "Card-Sales Response to Merchant Contactless Payment Acceptance: Causal Evidence," Working Papers hal-02296302, HAL.
    16. Gonçalves, S. & Rodrigues, T.P. & Chagas, A.L.S., 2020. "The impact of wind power on the Brazilian labor market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).

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    More about this item

    Keywords

    Quantile treatment effects; Copula; Panel data;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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