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Alternative Approaches to Evaluation in Empirical Microeconomics

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Author Info
Richard Blundell () (University College London and Institute for Fiscal Studies)
Mónica Costa Dias () (CETE, Faculdade de Economia - Universidade do Porto and Institute for Fiscal Studies)

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Abstract

This paper reviews a range of the most popular policy evaluation methods in empirical microeconomics: social experiments, natural experiments, matching methods, instrumental variables, discontinuity design and control functions. It discusses the identification of both the traditionally used average parameters and more complex distributional parameters. In each case, the necessary assumptions and the data requirements are considered. The adequacy of each approach is discussed drawing on the empirical evidence from the education and labor market policy evaluation literature. We also develop an education evaluation model which we use to carry through the discussion of each alternative approach. A full set of STATA datasets are provided free online which contain Monte-Carlo replications of the various specifications of the education evaluation model. There are also a full set of STATA .do files for each of the estimation approaches described in the paper. The .do-files can be used together with the datasets to reproduce all the results in the paper.

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Publisher Info
Paper provided by Universidade do Porto, Faculdade de Economia do Porto in its series CETE Discussion Papers with number 0805.

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Length: 125 pages
Date of creation: Oct 2008
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Handle: RePEc:por:cetedp:0805

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Related research
Keywords: Evaluation methods policy evaluation matching methods instrumental variables social experiments natural experiments difference-in-differences discontinuity design control function.

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Find related papers by JEL classification:
J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
J64 - Labor and Demographic Economics - - Mobility, Unemployment, and Vacancies - - - Unemployment: Models, Duration, Incidence, and Job Search
C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Heckman, James J, 1990. "Varieties of Selection Bias," American Economic Review, American Economic Association, vol. 80(2), pages 313-18, May.
  2. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  3. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January. [Downloadable!] (restricted)
  4. Richard Blundell & Alan Duncan & Costas Meghir, 1998. "Estimating Labor Supply Responses Using Tax Reforms," Econometrica, Econometric Society, vol. 66(4), pages 827-862, July.
    Other versions:
  5. Gary Burtless, 1985. "Are targeted wage subsidies harmful? Evidence from a wage voucher experiment," Industrial and Labor Relations Review, ILR Review, ILR School, Cornell University, vol. 39(1), pages 105-114, October.
  6. Bassi, Laurie J, 1984. "Estimating the Effect of Training Programs with Non-Random Selection," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 36-43, February. [Downloadable!] (restricted)
  7. Eissa, Nada & Liebman, Jeffrey B, 1996. "Labor Supply Response to the Earned Income Tax Credit," The Quarterly Journal of Economics, MIT Press, vol. 111(2), pages 605-37, May. [Downloadable!] (restricted)
    Other versions:
  8. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Blackwell Publishing, vol. 65(2), pages 261-94, April. [Downloadable!] (restricted)
  9. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-75, March. [Downloadable!] (restricted)
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  10. Alberto Abadie & Joshua D. Angrist & Guido W. Imbens, 1998. "Instrumental Variables Estimation of Quantile Treatment Effects," NBER Technical Working Papers 0229, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  11. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February. [Downloadable!] (restricted)
  12. Richard Blundell & Monica Costa Dias & Costas Meghir & John Van Reenen, 2001. "Evaluating the employment impact of a mandatory job search assistance program," IFS Working Papers W01/20, Institute for Fiscal Studies. [Downloadable!]
  13. Ashenfelter, Orley & Card, David, 1985. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 648-60, November. [Downloadable!] (restricted)
    Other versions:
  14. Jinyong Hahn, 1998. "On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects," Econometrica, Econometric Society, vol. 66(2), pages 315-332, March.
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