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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 Environments

In: Handbook of Econometrics

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Author Info
James J. Heckman
Vytlacil, Edward J.

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Abstract

This chapter uses the marginal treatment effect (MTE) to unify and organize the econometric literature on the evaluation of social programs. The marginal treatment effect is a choice-theoretic parameter that can be interpreted as a willingness to pay parameter for persons at a margin of indifference between participating in an activity or not. All of the conventional treatment parameters as well as the more economically motivated treatment effects can be generated from a baseline marginal treatment effect. All of the estimation methods used in the applied evaluation literature, such as matching, instrumental variables, regression discontinuity methods, selection and control function methods, make assumptions about the marginal treatment effect which we exposit. Models for multiple outcomes are developed. Empirical examples of the leading methods are presented. Methods are presented for bounding treatment effects in partially identified models, when the marginal treatment effect is known only over a limited support. We show how to use the marginal treatment in econometric cost benefit analysis, in defining limits of policy experiments, in constructing the average marginal treatment effect, and in forecasting the effects of programs in new environments.

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This chapter was published in: J.J. Heckman & E.E. Leamer (ed.) Handbook of Econometrics, , chapter 71, 2007.

This item is provided by Elsevier in its series Handbook of Econometrics with number 6b-71.

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This chapter was published in the following book, which is listed on IDEAS:
J.J. Heckman & E.E. Leamer (ed.), 2007. "Handbook of Econometrics," Handbook of Econometrics, Elsevier, edition 1, volume 6, number 6b. [Downloadable!] (restricted)
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C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

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This page was last updated on 2008-10-3.


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