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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, with much debate about whether some covariate is or is not a "valid instrument" in an application of interest. There is therefore good reason to consider weaker but more credible assumptions. assumptions. To this end, we introduce monotone instrumental variable (MIV) A particularly interesting special case of an MIV assumption is monotone treatment selection (MTS). IV and MIV assumptions may be imposed alone or in combination with other assumptions. We study the identifying power of MIV assumptions in three informational settings: MIV alone; MIV combined with the classical linear response assumption; MIV combined with the monotone treatment response (MTR) assumption. We apply the results to the problem of inference on the returns to schooling. We analyze wage data reported by white male respondents to the National Longitudinal Survey of Youth (NLSY) and use the respondent's AFQT score as an MIV. We find that this MIV assumption has little identifying power when imposed alone. However combining the MIV assumption with the MTR and MTS assumptions yields fairly tight bounds on two distinct measures of the returns to schooling.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0224.

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Date of creation: Feb 1998
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Handle: RePEc:nbr:nberte:0224

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  1. Blakemore, Arthur E. & Low, Stuart A., 1984. "The high-school dropout decision and its wage consequences," Economics of Education Review, Elsevier, vol. 3(2), pages 111-119, April.
  2. Joshua Angrist & Alan Krueger, 1990. "Does Compulsory School Attendance Affect Schooling and Earnings?," Working Papers 653, Princeton University, Department of Economics, Industrial Relations Section..
  3. Manski, Charles F, 1990. "Nonparametric Bounds on Treatment Effects," American Economic Review, American Economic Association, vol. 80(2), pages 319-23, May.
  4. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February.
  5. 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.
  6. David Card, 1994. "Earnings, Schooling, and Ability Revisited," Working Papers 710, Princeton University, Department of Economics, Industrial Relations Section..
  7. repec:fth:prinin:331 is not listed on IDEAS
  8. Joshua D. Angrist & Guido W. Imbens, 1995. "Identification and Estimation of Local Average Treatment Effects," NBER Technical Working Papers 0118, National Bureau of Economic Research, Inc.
  9. Robert J. Willis & Sherwin Rosen, 1978. "Education and Self-Selection," NBER Working Papers 0249, National Bureau of Economic Research, Inc.
  10. McKinley L. Blackburn & David Neumark, 1993. "Are OLS Estimates of the Return to Schooling Biased Downward? Another Look," NBER Working Papers 4259, National Bureau of Economic Research, Inc.
  11. Charles F. Manski, 1997. "Monotone Treatment Response," Econometrica, Econometric Society, vol. 65(6), pages 1311-1334, November.
  12. Oosterbeek, Hessel, 1990. "Education and earnings in the Netherlands: an empirical analysis," European Economic Review, Elsevier, vol. 34(7), pages 1353-1375, November.
  13. 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 775-89, October.
  14. Ashenfelter, Orley & Krueger, Alan B, 1994. "Estimates of the Economic Returns to Schooling from a New Sample of Twins," American Economic Review, American Economic Association, vol. 84(5), pages 1157-73, December.
  15. 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.
  16. 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.
  17. 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.
  18. Manski, C.F., 1990. "The Selection Problem," Working papers 90-12, Wisconsin Madison - Social Systems.
  19. 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 521-44, July.
  20. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc.
  21. Heckman, James J. & Robb, Richard Jr., 1985. "Alternative methods for evaluating the impact of interventions : An overview," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 239-267.
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