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Beyond Plausibly Exogenous

Author

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  • Hans (J.L.W.) van Kippersluis

    (Erasmus School of Economics, The Netherlands; Tinbergen Institute, The Netherlands)

  • Niels (C.A.) Rietveld

    (Erasmus School of Economics, The Netherlands)

Abstract

We synthesize two recent advances in the literature on instrumental variables (IVs) estimation that test and relax the exclusion restriction. Our approach first estimates the direct effect of the IV on the outcome in a subsample for which the IV does not affect the treatment variable. Subsequently, this estimate for the direct effect is used as input for the plausibly exogenous method developed by Conley, Hansen and Rossi (2012). This two-step procedure provides a novel and informed sensitivity analysis for IV estimation. We illustrate the practical use by estimating the causal effect of (i) attending Catholic high school on schooling outcomes, and (ii) the number of children on female labour supply.

Suggested Citation

  • Hans (J.L.W.) van Kippersluis & Niels (C.A.) Rietveld, 2017. "Beyond Plausibly Exogenous," Tinbergen Institute Discussion Papers 17-096/V, Tinbergen Institute.
  • Handle: RePEc:tin:wpaper:20170096
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    References listed on IDEAS

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    1. Mark Dincecco & Mauricio Prado, 2012. "Warfare, fiscal capacity, and performance," Journal of Economic Growth, Springer, vol. 17(3), pages 171-203, September.
    2. Michal Kolesár & Raj Chetty & John Friedman & Edward Glaeser & Guido W. Imbens, 2015. "Identification and Inference With Many Invalid Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 474-484, October.
    3. Aviv Nevo & Adam M. Rosen, 2012. "Identification With Imperfect Instruments," The Review of Economics and Statistics, MIT Press, vol. 94(3), pages 659-671, August.
    4. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records," American Economic Review, American Economic Association, vol. 80(3), pages 313-336, June.
    5. Andrews,Donald W. K. & Stock,James H. (ed.), 2005. "Identification and Inference for Econometric Models," Cambridge Books, Cambridge University Press, number 9780521844413.
    6. John Bound & David A. Jaeger, 1996. "On the Validity of Season of Birth as an Instrument in Wage Equations: A Comment on Angrist & Krueger's "Does Compulsory School Attendance Affect Scho," NBER Working Papers 5835, National Bureau of Economic Research, Inc.
    7. Amy Finkelstein & Sarah Taubman & Bill Wright & Mira Bernstein & Jonathan Gruber & Joseph P. Newhouse & Heidi Allen & Katherine Baicker, 2012. "The Oregon Health Insurance Experiment: Evidence from the First Year," The Quarterly Journal of Economics, Oxford University Press, vol. 127(3), pages 1057-1106.
    8. Timothy G. Conley & Christian B. Hansen & Peter E. Rossi, 2012. "Plausibly Exogenous," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 260-272, February.
    9. Richard Ashley, 2009. "Assessing the credibility of instrumental variables inference with imperfect instruments via sensitivity analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 325-337, March.
    10. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    11. Nathan Nunn & Leonard Wantchekon, 2011. "The Slave Trade and the Origins of Mistrust in Africa," American Economic Review, American Economic Association, vol. 101(7), pages 3221-3252, December.
    12. Small, Dylan S., 2007. "Sensitivity Analysis for Instrumental Variables Regression With Overidentifying Restrictions," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1049-1058, September.
    13. Joshua Angrist & Victor Lavy & Analia Schlosser, 2010. "Multiple Experiments for the Causal Link between the Quantity and Quality of Children," Journal of Labor Economics, University of Chicago Press, vol. 28(4), pages 773-824, October.
    14. Jinyong Hahn & Jerry Hausman, 2002. "A New Specification Test for the Validity of Instrumental Variables," Econometrica, Econometric Society, vol. 70(1), pages 163-189, January.
    15. Ding, Weili & Lehrer, Steven F. & Rosenquist, J.Niels & Audrain-McGovern, Janet, 2009. "The impact of poor health on academic performance: New evidence using genetic markers," Journal of Health Economics, Elsevier, vol. 28(3), pages 578-597, May.
    16. Damon Jones, 2015. "The Economics of Exclusion Restrictions in IV Models," NBER Working Papers 21391, National Bureau of Economic Research, Inc.
    17. Joshua D. Angrist & Jörn-Steffen Pischke, 2015. "The path from cause to effect: mastering 'metrics," CentrePiece - The magazine for economic performance 442, Centre for Economic Performance, LSE.
    18. Carlos A. Flores & Alfonso Flores-Lagunes, 2013. "Partial Identification of Local Average Treatment Effects With an Invalid Instrument," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(4), pages 534-545, October.
    19. Aart Kraay, 2012. "Instrumental variables regressions with uncertain exclusion restrictions: a Bayesian approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(1), pages 108-128, January.
    20. Angrist, Joshua D, 1990. "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records: Errata," American Economic Review, American Economic Association, vol. 80(5), pages 1284-1286, December.
    21. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "An Evaluation of Instrumental Variable Strategies for Estimating the Effects of Catholic Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 40(4), pages 791-821.
    22. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 979-1014.
    23. Damian Clarke, 2014. "PLAUSEXOG: Stata module to implement Conley et al's plausibly exogenous bounds," Statistical Software Components S457832, Boston College Department of Economics, revised 08 Jul 2020.
    24. Berkowitz, Daniel & Caner, Mehmet & Fang, Ying, 2012. "The validity of instruments revisited," Journal of Econometrics, Elsevier, vol. 166(2), pages 255-266.
    25. Hyunseung Kang & Anru Zhang & T. Tony Cai & Dylan S. Small, 2016. "Instrumental Variables Estimation With Some Invalid Instruments and its Application to Mendelian Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 132-144, March.
    26. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
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    More about this item

    Keywords

    Instrumental variables; plausibly exogenous; exclusion restriction;
    All these keywords.

    JEL classification:

    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General

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