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Program Evaluation and Research Designs

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  • DiNardo, John
  • Lee, David S.

Abstract

This chapter provides a selective review of some contemporary approaches to program evaluation. One motivation for our review is the recent emergence and increasing use of a particular kind of "program" in applied microeconomic research, the so-called Regression Discontinuity (RD) Design of Thistlethwaite and Campbell (1960). We organize our discussion of these various research designs by how they secure internal validity: in this view, the RD design can been seen as a close "cousin" of the randomized experiment. An important distinction which emerges from our discussion of "heterogeneous treatment effects" is between ex post (descriptive) and ex ante (predictive) evaluations; these two types of evaluations have distinct, but complementary goals. A second important distinction we make is between statistical statements that are descriptions of our knowledge of the program assignment process and statistical statements that are structural assumptions about individual behavior. Using these distinctions,we examine some commonly employed evaluation strategies, and assess them with a common set of criteria for "internal validity", the foremost goal of an ex post evaluation. In some cases, we also provide some concrete illustrations of how internally valid causal estimates can be supplemented with specific structural assumptions to address "external validity": the estimate from an internally valid "experimental" estimate can be viewed as a "leading term" in an extrapolation for a parameter of interest in an ex ante evaluation.

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This chapter was published in:

  • O. Ashenfelter & D. Card (ed.), 2011. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 4, number 4.
    This item is provided by Elsevier in its series Handbook of Labor Economics with number 4-05.

    Handle: RePEc:eee:labchp:4-05

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    Web page: http://www.elsevier.com/wps/find/bookseriesdescription.cws_home/BS_HE/description

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    Cited by:
    1. David E. Card & Pablo Ibarraran & Juan Miguel Villa, 2011. "Building in an Evaluation Component for Active Labor Market Programs: A Practitioner's Guide," SPD Working Papers 1101, Inter-American Development Bank, Office of Strategic Planning and Development Effectiveness (SPD).
    2. Jens Ludwig & Jeffrey R. Kling & Sendhil Mullainathan, 2011. "Mechanism Experiments and Policy Evaluations," NBER Working Papers 17062, National Bureau of Economic Research, Inc.
    3. Matthew D. Webb, 2013. "Reworking Wild Bootstrap Based Inference for Clustered Errors," Working Papers 1315, Queen's University, Department of Economics.
    4. Chaisemartin, Clément de, 2014. "Tolerating defiance? Local average treatment effects without monotonicity," CAGE Online Working Paper Series 197, Competitive Advantage in the Global Economy (CAGE).
    5. Nicholas Bloom & John Van Reenen, 2010. "Human Resource Management and Productivity," NBER Working Papers 16019, National Bureau of Economic Research, Inc.
    6. Harding, Matthew & Lamarche, Carlos, 2014. "Estimating and testing a quantile regression model with interactive effects," Journal of Econometrics, Elsevier, vol. 178(P1), pages 101-113.
    7. Doyle, Joseph J., 2013. "Causal effects of foster care: An instrumental-variables approach," Children and Youth Services Review, Elsevier, vol. 35(7), pages 1143-1151.
    8. de Chaisemartin, Clement, 2013. "Defying the LATE? Identification of local treatment effects when the instrument violates monotonicity," The Warwick Economics Research Paper Series (TWERPS) 1020, University of Warwick, Department of Economics.
    9. Arni, Patrick, 2012. "Kausale Evaluation von Pilotprojekten: Die Nutzung von Randomisierung in der Praxis," IZA Standpunkte 52, Institute for the Study of Labor (IZA).

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    1. Labor Economics (ECON 531)

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