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From Late to MTE: Alternative Methods for the Evaluation of Policy Interventions

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  • Cornelissen, Thomas
  • Dustmann, Christian
  • Raute, Anna
  • Schönberg, Uta

Abstract

This paper provides an introduction into the estimation of Marginal Treatment Effects (MTE). Compared to the existing surveys on the subject, our paper is less technical and speaks to the applied economist with a solid basic understanding of econometric techniques who would like to use MTE estimation. Our framework of analysis is a generalized Roy model based on the potential outcomes framework, within which we define different treatment effects of interest, and review the well-known case of IV estimation with a discrete instrument resulting in a local average treatment effect (LATE). Turning to IV estimation with a continuous instrument we demonstrate that the 2SLS estimator may be viewed as a weighted average of LATEs, and discuss MTE estimation as an alternative and more informative way of exploiting a continuous instrument. We clarify the assumptions underlying the MTE framework and illustrate how the MTE estimation is implemented in practice.

Suggested Citation

  • Cornelissen, Thomas & Dustmann, Christian & Raute, Anna & Schönberg, Uta, 2016. "From Late to MTE: Alternative Methods for the Evaluation of Policy Interventions," CEPR Discussion Papers 11390, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11390
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    as
    1. Joseph J. Doyle Jr., 2007. "Child Protection and Child Outcomes: Measuring the Effects of Foster Care," American Economic Review, American Economic Association, vol. 97(5), pages 1583-1610, December.
    2. James J. Heckman & Vytlacil, Edward J., 2007. "Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New," Handbook of Econometrics,in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 71 Elsevier.
    3. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492 National Bureau of Economic Research, Inc.
    4. Angus Deaton, 2009. "Instruments of development: Randomization in the tropics, and the search for the elusive keys to economic development," Working Papers 1128, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
    5. repec:spr:portec:v:1:y:2002:i:2:d:10.1007_s10258-002-0010-3 is not listed on IDEAS
    6. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    7. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    8. Katja Maria Kaufmann, 2014. "Understanding the income gradient in college attendance in Mexico: The role of heterogeneity in expected returns," Quantitative Economics, Econometric Society, vol. 5(3), pages 583-630, November.
    9. Colm Harmon; & Ian Walker, 1995. "Estimates of Economic Return to Schooling in the UK," Economics, Finance and Accounting Department Working Paper Series n540195, Department of Economics, Finance and Accounting, National University of Ireland - Maynooth.
    10. Patrick Kline & Christopher R. Walters, 2016. "Evaluating Public Programs with Close Substitutes: The Case of HeadStart," The Quarterly Journal of Economics, Oxford University Press, vol. 131(4), pages 1795-1848.
    11. Juanna Schrøter Joensen & Helena Skyt Nielsen, 2016. "Mathematics and Gender: Heterogeneity in Causes and Consequences," Economic Journal, Royal Economic Society, vol. 126(593), pages 1129-1163, June.
    12. 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.
    13. Pedro Carneiro & James J. Heckman & Edward J. Vytlacil, 2011. "Estimating Marginal Returns to Education," American Economic Review, American Economic Association, vol. 101(6), pages 2754-2781, October.
    14. Kamhöfer, Daniel A. & Schmitz, Hendrik & Westphal, Matthias, 2015. "Heterogeneity in marginal non-monetary returns to higher education," Ruhr Economic Papers 591, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    15. Heckman, James J. & Urzúa, Sergio, 2010. "Comparing IV with structural models: What simple IV can and cannot identify," Journal of Econometrics, Elsevier, vol. 156(1), pages 27-37, May.
    16. Harmon, Colm & Walker, Ian, 1995. "Estimates of the Economic Return to Schooling for the United Kingdom," American Economic Review, American Economic Association, vol. 85(5), pages 1278-1286, December.
    17. Lee, Lung-Fei, 1979. "Identification and Estimation in Binary Choice Models with Limited (Censored) Dependent Variables," Econometrica, Econometric Society, vol. 47(4), pages 977-996, July.
    18. Grace E. Noboa-Hidalgo & Sergio S. Urzúa, 2012. "The Effects of Participation in Public Child Care Centers: Evidence from Chile," Journal of Human Capital, University of Chicago Press, vol. 6(1), pages 1-34.
    19. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769, June.
    20. Eric French & Jae Song, 2014. "The Effect of Disability Insurance Receipt on Labor Supply," American Economic Journal: Economic Policy, American Economic Association, vol. 6(2), pages 291-337, May.
    21. Edward Vytlacil & James J. Heckman, 2001. "Policy-Relevant Treatment Effects," American Economic Review, American Economic Association, vol. 91(2), pages 107-111, May.
    22. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    23. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    24. Anirban Basu & Andrew M. Jones & Pedro Rosa Dias, 2014. "The Roles of Cognitive and Non-Cognitive Skills in Moderating the Effects of Mixed-Ability Schools on Long-Term Health," NBER Working Papers 20811, National Bureau of Economic Research, Inc.
    25. Nicole Maestas & Kathleen J. Mullen & Alexander Strand, 2013. "Does Disability Insurance Receipt Discourage Work? Using Examiner Assignment to Estimate Causal Effects of SSDI Receipt," American Economic Review, American Economic Association, vol. 103(5), pages 1797-1829, August.
    26. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics,in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
    27. Angrist, Joshua D., 1991. "Grouped-data estimation and testing in simple labor-supply models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 243-266, February.
    28. repec:ucp:jlabec:doi:10.1086/692475 is not listed on IDEAS
    29. Scott Brave & Thomas Walstrum, 2014. "Estimating marginal treatment effects using parametric and semiparametric methods," Stata Journal, StataCorp LP, vol. 14(1), pages 191-217, March.
    30. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    31. James Heckman & Edward Vytlacil, 1998. "Instrumental Variables Methods for the Correlated Random Coefficient Model: Estimating the Average Rate of Return to Schooling When the Return is Correlated with Schooling," Journal of Human Resources, University of Wisconsin Press, vol. 33(4), pages 974-987.
    32. Martin Nybom, 2017. "The Distribution of Lifetime Earnings Returns to College," Journal of Labor Economics, University of Chicago Press, vol. 35(4), pages 903-952.
    33. Philip Oreopoulos, 2006. "Estimating Average and Local Average Treatment Effects of Education when Compulsory Schooling Laws Really Matter," American Economic Review, American Economic Association, vol. 96(1), pages 152-175, March.
    34. Philipp Eisenhauer & James J. Heckman & Edward Vytlacil, 2015. "The Generalized Roy Model and the Cost-Benefit Analysis of Social Programs," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 413-443.
    35. repec:ucp:jpolec:doi:10.1086/692712 is not listed on IDEAS
    36. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1133-1157.
    37. 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.
    38. Raj Chetty & Nathaniel Hendren & Lawrence F. Katz, 2016. "The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment," American Economic Review, American Economic Association, vol. 106(4), pages 855-902, April.
    39. French, Eric & Taber, Christopher, 2011. "Identification of Models of the Labor Market," Handbook of Labor Economics, Elsevier.
    40. 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.
    41. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
    42. Harmon, Harmon & Ian Walker, 1995. "Estimates of the economic return to schooling for the UK," IFS Working Papers W95/12, Institute for Fiscal Studies.
    43. Card, David, 2001. "Estimating the Return to Schooling: Progress on Some Persistent Econometric Problems," Econometrica, Econometric Society, vol. 69(5), pages 1127-1160, September.
    44. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients," Health, Econometrics and Data Group (HEDG) Working Papers 07/07, HEDG, c/o Department of Economics, University of York.
    45. Jeffrey M. Wooldridge, 2015. "Control Function Methods in Applied Econometrics," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 420-445.
    46. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
    47. 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.
    48. repec:hrv:faseco:30367426 is not listed on IDEAS
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    Cited by:

    1. repec:eee:pubeco:v:159:y:2018:i:c:p:33-53 is not listed on IDEAS
    2. Thomas Cornelissen & Christian Dustmann & Anna Raute & Uta Schönberg, 2018. "Who benefits from universal child care? Estimating marginal returns to early child care attendance," CReAM Discussion Paper Series 1808, Centre for Research and Analysis of Migration (CReAM), Department of Economics, University College London.
    3. Huber, Martin & Wüthrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.

    More about this item

    Keywords

    heterogeneous effects; instrumental variables; marginal treatment effects;

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I26 - Health, Education, and Welfare - - Education - - - Returns to Education

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