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Monotone Instrumental Variables, with an Application to the Returns to Schooling

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  • Charles F. Manski
  • John V. Pepper

Abstract

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects. Yet the credibility of IV assumptions is often a matter of considerable disagreement. There is therefore good reason to consider weaker but more credible assumptions. To this end, we introduce monotone instrumental variable (MIV) assumptions and the important special case of monotone treatment selection (MTS). We study the identifying power of MIV assumptions alone and combined with the assumption of monotone treatment response (MTR). We present an empirical application using the MTS and MTR assumptions to place upper bounds on the returns to schooling.
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Suggested Citation

  • Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
  • Handle: RePEc:ecm:emetrp:v:68:y:2000:i:4:p:997-1012
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    References listed on IDEAS

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    1. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-323, May.
    2. John V. Pepper, 2000. "The Intergenerational Transmission Of Welfare Receipt: A Nonparametric Bounds Analysis," The Review of Economics and Statistics, MIT Press, vol. 82(3), pages 472-488, August.
    3. Willis, Robert J & Rosen, Sherwin, 1979. "Education and Self-Selection," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 7-36, October.
    4. Blackburn, McKinley L & Neumark, David, 1995. "Are OLS Estimates of the Return to Schooling Biased Downward? Another Look," The Review of Economics and Statistics, MIT Press, vol. 77(2), pages 217-230, May.
    5. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    6. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
    7. Lang, Kevin & Ruud, Paul A, 1986. "Returns to Schooling, Implicit Discount Rates and Black-White Wage Differentials," The Review of Economics and Statistics, MIT Press, vol. 68(1), pages 41-47, February.
    8. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
    9. Kenny, Lawrence W, et al, 1979. "Returns to College Education: An Investigation of Self-Selection Bias Based on the Project Talent Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(3), pages 775-789, October.
    10. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
    11. Charles F. Manski, 1996. "Learning about Treatment Effects from Experiments with Random Assignment of Treatments," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 709-733.
    12. Garen, John, 1984. "The Returns to Schooling: A Selectivity Bias Approach with a Continuous Choice Variable," Econometrica, Econometric Society, vol. 52(5), pages 1199-1218, September.
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    17. Blackburn, McKinley L & Neumark, David, 1993. "Omitted-Ability Bias and the Increase in the Return to Schooling," Journal of Labor Economics, University of Chicago Press, vol. 11(3), pages 521-544, July.
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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