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Supplement to Fuzzy Differences-in-Differences

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  • de Chaisemartin, Clement
  • D'Haultfoeuille, Xavier

Abstract

This paper gathers the supplementary material to de Chaisemartin & D'Haultf÷uille (2015). First, we show that two commonly used IV and OLS regressions with time and group xed eects estimate weighted averages of Wald-DIDs. It then follows from Theorem 3.1 in de Chaisemartin & D'Haultf÷uille (2015) that these regressions estimate weighted sums of LATEs, with potentially many negative weights as we illustrate through two applications. We review all papers published in the American Economic Review between 2010 and 2012 and nd that 10.1% of these papers estimate one or the other regression. Second, we consider estimators of the bounds on average and quantile treatment eects derived in Theorems 3.2 and 3.3 in de Chaisemartin & D'Haultf÷uille (2015) and we study their asymptotic behavior. Third, we revisit Gentzkow et al. (2011) and Field (2007) using our estimators. Finally, we present all the remaining proofs not included in the main paper.

Suggested Citation

  • de Chaisemartin, Clement & D'Haultfoeuille, Xavier, "undated". "Supplement to Fuzzy Differences-in-Differences," Economic Research Papers 270217, University of Warwick - Department of Economics.
    • Handle: RePEc:ags:uwarer:270217
    DOI: 10.22004/ag.econ.270217
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    1. Ruben Enikolopov & Maria Petrova & Ekaterina Zhuravskaya, 2011. "Media and Political Persuasion: Evidence from Russia," American Economic Review, American Economic Association, vol. 101(7), pages 3253-3285, December.
    2. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, vol. 81(2), pages 667-737, March.
    3. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2014. "A Practical Two‐Step Method for Testing Moment Inequalities," Econometrica, Econometric Society, vol. 82, pages 1979-2002, September.
    4. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, January.
    5. C de Chaisemartin & X D’HaultfŒuille, 2018. "Fuzzy Differences-in-Differences," Review of Economic Studies, Oxford University Press, vol. 85(2), pages 999-1028.
    6. Field, Erica Marie, 2005. "Property Rights and Investment in Urban Slums," Scholarly Articles 3634150, Harvard University Department of Economics.
    7. Erica Field, 2007. "Entitled to Work: Urban Property Rights and Labor Supply in Peru," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(4), pages 1561-1602.
    8. Donald W. K. Andrews & Gustavo Soares, 2010. "Inference for Parameters Defined by Moment Inequalities Using Generalized Moment Selection," Econometrica, Econometric Society, vol. 78(1), pages 119-157, January.
    9. Donald W. K. Andrews & Panle Jia Barwick, 2012. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Econometrica, Econometric Society, vol. 80(6), pages 2805-2826, November.
    10. Jorg Stoye, 2009. "More on Confidence Intervals for Partially Identified Parameters," Econometrica, Econometric Society, vol. 77(4), pages 1299-1315, July.
    11. Erica Field, 2005. "Property Rights and Investment in Urban Slums," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 279-290, 04/05.
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    More about this item

    Keywords

    Financial Economics;

    JEL classification:

    • 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

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