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Assessing the performance of matching algorithms when selection into treatment is strong

  • Jochen Kluve


  • Boris Augurzky


This paper investigates the method of matching regarding two crucial implementation choices, the distance measure and the type of algorithm.We implement optimal full matching – a fully efficient algorithm – and present a framework for statistical inference. The implementation uses data from the NLSY79 to study the effect of college education on earnings. We find that decisions regarding the matching algorithm depend on the structure of the data: In the case of strong selection into treatment and treatment effect heterogeneity a full matching seems preferable. If heterogeneity is weak, pair matching suffices.

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Paper provided by Rheinisch-Westfälisches Institut für Wirtschaftsforschung in its series RWI Discussion Papers with number 0021.

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Length: 42 pages
Date of creation: Sep 2005
Date of revision:
Handle: RePEc:rwi:dpaper:0021
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  1. Kluve, Jochen & Lehmann, Hartmut & Schmidt, Christoph M, 1999. "Active Labour Market Policies in Poland: Human Capital Enhancement, Stigmatization or Benefit Churning?," CEPR Discussion Papers 2059, C.E.P.R. Discussion Papers.
  2. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  3. 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.
  4. Joshua D. Angrist, 1998. "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants," Econometrica, Econometric Society, vol. 66(2), pages 249-288, March.
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