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IV Quantile Regression for Group-level Treatments, with an Application to the Distributional Effects of Trade

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  • Denis Chetverikov
  • Bradley Larsen
  • Christopher Palmer

Abstract

We present a methodology for estimating the distributional effects of an endogenous treatment that varies at the group level when there are group-level unobservables, a quantile extension of Hausman and Taylor (1981). Because of the presence of group-level unobservables, standard quantile regression techniques are inconsistent in our setting even if the treatment is independent of unobservables. In contrast, our estimation technique is consistent as well as computationally simple, consisting of group-by-group quantile regression followed by two-stage least squares. Using the Bahadur representation of quantile estimators, we derive weak conditions on the growth of the number of observations per group that are sufficient for consistency and asymptotic zero-mean normality of our estimator. As in Hausman and Taylor (1981), micro-level covariates can be used as internal instruments for the endogenous group-level treatment if they satisfy relevance and exogeneity conditions. An empirical application indicates that low-wage earners in the US from 1990--2007 were significantly more affected by increased Chinese import competition than high-wage earners. Our approach applies to a broad range of settings in labor, industrial organization, trade, public finance, and other applied fields.

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  • Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2015. "IV Quantile Regression for Group-level Treatments, with an Application to the Distributional Effects of Trade," NBER Working Papers 21033, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21033
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    Citations

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    Cited by:

    1. Elhanan Helpman, 2016. "Globalization and Wage Inequality," NBER Working Papers 22944, National Bureau of Economic Research, Inc.
    2. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. repec:eee:jhecon:v:56:y:2017:i:c:p:383-396 is not listed on IDEAS
    4. David Autor & David Dorn & Gordon Hanson, 2017. "When Work Disappears: Manufacturing Decline and the Falling Marriage-Market Value of Young Men," NBER Working Papers 23173, National Bureau of Economic Research, Inc.
    5. Alexander Murray, 2017. "The Effect of Import Competition on Employment in Canada: Evidence from the 'China Shock'," CSLS Research Reports 2017-03, Centre for the Study of Living Standards.
    6. Kumar, Anil, 2017. "Does Medicaid Generosity Affect Household Income?," Working Papers 1709, Federal Reserve Bank of Dallas, revised 01 Apr 2018.
    7. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    8. Stephen Sheppard & Dan Zhao, 2016. "Regional Concentration of Industry in China: Decentralised Choices or a Central Plan?," Department of Economics Working Papers 2016-17, Department of Economics, Williams College.
    9. David H. Autor & David Dorn & Gordon H. Hanson, 2016. "The China Shock: Learning from Labor-Market Adjustment to Large Changes in Trade," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 205-240, October.
    10. Decarolis, Francesco & Guglielmo, Andrea, 2017. "Insurers’ response to selection risk: Evidence from Medicare enrollment reforms," Journal of Health Economics, Elsevier, vol. 56(C), pages 383-396.
    11. Shushanik Hakobyan & John McLaren, 2018. "NAFTA and the Wages of Married Women," NBER Working Papers 24424, National Bureau of Economic Research, Inc.
    12. repec:iza:izawol:journl:y:2018:n:431 is not listed on IDEAS
    13. Autor, David & Dorn, David & Hanson, Gordon, 2017. "When Work Disappears: Manufacturing Decline and the Falling Marriage-Market Value of Men," CEPR Discussion Papers 11878, C.E.P.R. Discussion Papers.

    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • 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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation
    • F16 - International Economics - - Trade - - - Trade and Labor Market Interactions
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General

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