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Bootstrap inference for K-nearest neighbour matching estimators

  • de Luna, Xavier

    ()

    (Umeå University)

  • Johansson, Per

    ()

    (IFAU - Institute for Labour Market Policy Evaluation)

  • Sjöstedt-de Luna, Sara

    ()

    (Umeå University)

Abadie and Imbens (2008, Econometrica) showed that classical bootstrap schemes fail to provide correct inference for K-nearest neighbour (KNN) matching estimators of average causal effects. This is an interesting result showing that bootstrap should not be applied without theoretical justification. In this paper, we present two resampling schemes, which we show provide valid inference for KNN matching estimators. We resample "estimated individual causal effects" (EICE), i.e. the difference in outcome between matched pairs, instead of the original data. Moreover, by taking differences in EICEs ordered with respect to the matching covariate, we obtain a bootstrap scheme valid also with heterogeneous causal effects where mild assumptions on the heterogeneity are imposed. We provide proofs of the validity of the proposed resampling based inferences. A simulation study illustrates finite sample properties.

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Paper provided by IFAU - Institute for Evaluation of Labour Market and Education Policy in its series Working Paper Series with number 2010:13.

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Length: 24 pages
Date of creation: 19 Nov 2010
Date of revision:
Handle: RePEc:hhs:ifauwp:2010_013
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  1. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
  2. Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
  3. Ben B. Hansen, 2008. "The prognostic analogue of the propensity score," Biometrika, Biometrika Trust, vol. 95(2), pages 481-488.
  4. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
  5. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, 01.
  6. Ekstrom, Magnus & Luna, Sara Sjostedt-De, 2004. "Subsampling Methods to Estimate the Variance of Sample Means Based on Nonstationary Spatial Data With Varying Expected Values," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 82-95, January.
  7. Sjöstedt-de Luna, 2005. "Some properties of weakly approaching sequences of distributions," Statistics & Probability Letters, Elsevier, vol. 75(2), pages 119-126, November.
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