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Distributional Policy Effects with Many Treatment Outcomes

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  • Cañón Salazar Carlos Iván

Abstract

Different segments of a population affected by the same policy intervention may have different responses. We study the role of equilibrium effects on explaining these differences. Our case study is the government's extension of guarantees during the Great Recession to certain debt issuers. We extend Athey and Imbens [2006] to a scenario of multiple outcome variables, and identify the counterfactual joint distribution. We find the intervention increased the funding for the treated segments, but at the cost of higher spreads. Finally, these equilibrium effects operate dissimilarly along the segments of the treated group, in the extreme, can produce undesired effects.

Suggested Citation

  • Cañón Salazar Carlos Iván, 2016. "Distributional Policy Effects with Many Treatment Outcomes," Working Papers 2016-01, Banco de México.
  • Handle: RePEc:bdm:wpaper:2016-01
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    References listed on IDEAS

    as
    1. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
    2. Armantier, Olivier & Ghysels, Eric & Sarkar, Asani & Shrader, Jeffrey, 2015. "Discount window stigma during the 2007–2008 financial crisis," Journal of Financial Economics, Elsevier, vol. 118(2), pages 317-335.
    3. Murillo Campello & Erasmo Giambona & John R. Graham & Campbell R. Harvey, 2011. "Liquidity Management and Corporate Investment During a Financial Crisis," The Review of Financial Studies, Society for Financial Studies, vol. 24(6), pages 1944-1979.
    4. Stéphane Bonhomme & Ulrich Sauder, 2011. "Recovering Distributions in Difference-in-Differences Models: A Comparison of Selective and Comprehensive Schooling," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 479-494, May.
    5. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    6. Abadie, Alberto, 2003. "Semiparametric instrumental variable estimation of treatment response models," Journal of Econometrics, Elsevier, vol. 113(2), pages 231-263, April.
    7. Kahle, Kathleen M. & Stulz, Rene M., 2010. "Financial Policies and the Financial Crisis: How Important Was the Systemic Credit Contraction for Industrial Corporations?," Working Paper Series 2010-13, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    8. Sergio Firpo & Cristine Pinto, 2016. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 457-486, April.
    9. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    10. Nelsen, Roger B. & Quesada-Molina, José Juan & Rodri­guez-Lallena, José Antonio & Úbeda-Flores, Manuel, 2008. "On the construction of copulas and quasi-copulas with given diagonal sections," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 473-483, April.
    11. Xiaohong Chen & Han Hong & Alessandro Tarozzi, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Cowles Foundation Discussion Papers 1644, Cowles Foundation for Research in Economics, Yale University.
    12. Jean Tirole, 2012. "Overcoming Adverse Selection: How Public Intervention Can Restore Market Functioning," American Economic Review, American Economic Association, vol. 102(1), pages 29-59, February.
    13. John A. Weinberg & Huberto M. Ennis, 2009. "A Model of Stigma in the Fed Funds Market," 2009 Meeting Papers 956, Society for Economic Dynamics.
    14. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Interventions; Stigma; Identification; Nonlinear Difference-In-Difference; Copulas;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

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