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Estimating the Veteran Effect with Endogenous Schooling When Instruments Are Potentially Weak

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  • Chaudhuri, Saraswata

    () (University of North Carolina, Chapel Hill)

  • Rose, Elaina

    () (University of Washington)

Abstract

Instrumental variables estimates of the effect of military service on subsequent civilian earnings either omit schooling or treat it as exogenous. In a more general setting that also allows for the treatment of schooling as endogenous, we estimate the veteran effect for men who were born between 1944 and 1952 and thus reached draft age during the Vietnam era. We apply a variety of state-of-the-art econometric techniques to gauge the sensitivity of the estimates to the treatment of schooling. We find a significant veteran penalty.

Suggested Citation

  • Chaudhuri, Saraswata & Rose, Elaina, 2009. "Estimating the Veteran Effect with Endogenous Schooling When Instruments Are Potentially Weak," IZA Discussion Papers 4203, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp4203
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    References listed on IDEAS

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    1. Kenneth I. Wolpin & Mark R. Rosenzweig, 2000. "Natural "Natural Experiments" in Economics," Journal of Economic Literature, American Economic Association, vol. 38(4), pages 827-874, December.
    2. Angrist, Joshua & Krueger, Alan B, 1994. "Why Do World War II Veterans Earn More Than Nonveterans?," Journal of Labor Economics, University of Chicago Press, vol. 12(1), pages 74-97, January.
    3. Angrist, Joshua & Chen, Stacey, 2008. "Long-Term Economic Consequences of Vietnam-Era Conscription: Schooling, Experience and Earnings," IZA Discussion Papers 3628, Institute for the Study of Labor (IZA).
    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. Matthew S. Goldberg & John T. Warner, 1987. "Military Experience, Civilian Experience, and the Earnings of Veterans," Journal of Human Resources, University of Wisconsin Press, vol. 22(1), pages 61-81.
    6. James H. Stock & Motohiro Yogo, 2002. "Testing for Weak Instruments in Linear IV Regression," NBER Technical Working Papers 0284, National Bureau of Economic Research, Inc.
    7. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    8. James H. Stock & Jonathan Wright, 2000. "GMM with Weak Identification," Econometrica, Econometric Society, vol. 68(5), pages 1055-1096, September.
    9. Card, David, 1999. "The causal effect of education on earnings," Handbook of Labor Economics,in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 30, pages 1801-1863 Elsevier.
    10. Sherwin Rosen & Paul Taubman, 1982. "Changes in Life-Cycle Earnings: What Do Social Security Data Show?," Journal of Human Resources, University of Wisconsin Press, vol. 17(3), pages 321-338.
    11. Kleibergen, Frank & Mavroeidis, Sophocles, 2009. "Weak Instrument Robust Tests in GMM and the New Keynesian Phillips Curve," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 293-311.
    12. Joshua D. Angrist & Alan B. Keueger, 1991. "Does Compulsory School Attendance Affect Schooling and Earnings?," The Quarterly Journal of Economics, Oxford University Press, vol. 106(4), pages 979-1014.
    13. John Shea, 1997. "Instrument Relevance in Multivariate Linear Models: A Simple Measure," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 348-352, May.
    14. De Tray, Dennis, 1982. "Veteran Status as a Screening Device," American Economic Review, American Economic Association, vol. 72(1), pages 133-142, March.
    15. Frank Kleibergen, 2005. "Testing Parameters in GMM Without Assuming that They Are Identified," Econometrica, Econometric Society, vol. 73(4), pages 1103-1123, July.
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    Cited by:

    1. Doko Tchatoka, Firmin, 2012. "On the Validity of Durbin-Wu-Hausman Tests for Assessing Partial Exogeneity Hypotheses with Possibly Weak Instruments," MPRA Paper 40184, University Library of Munich, Germany.
    2. Doko Tchatoka, Firmin Sabro, 2012. "Specification Tests with Weak and Invalid Instruments," MPRA Paper 40185, University Library of Munich, Germany.
    3. Deuchert, Eva & Huber, Martin, 2014. "A cautionary tale about control variables in IV estimation," FSES Working Papers 453, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    4. Christopher J. Bennett & Ričardas Zitikis, 2013. "Examining the Distributional Effects of Military Service on Earnings: A Test of Initial Dominance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(1), pages 1-15, January.
    5. repec:bla:obuest:v:79:y:2017:i:3:p:411-425 is not listed on IDEAS

    More about this item

    Keywords

    veteran effect; weak instruments;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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