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Multivariate Matching Methods That are Monotonic Imbalance Bounding


  • Stefano Iacus

    (Department of Economics, Business and Statistics, University of Milan, IT)

  • Gary King

    (Institute for Quantitative Social Science, Harvard University)

  • Giuseppe Porro

    (Department of Economics and Statistics, University of Trieste)


We introduce a new ``Monotonic Imbalance Bounding'' (MIB) class of matching methods for causal inference that satisfies several important in-sample properties. MIB generalizes and extends in several new directions the only existing class, ``Equal Percent Bias Reducing'' (EPBR), which is designed to satisfy weaker properties and only in expectation. We also offer strategies to obtain specific members of the MIB class, and present a member of this class, called Coarsened Exact Matching, whose properties we analyze from this new perspective.

Suggested Citation

  • Stefano Iacus & Gary King & Giuseppe Porro, 2009. "Multivariate Matching Methods That are Monotonic Imbalance Bounding," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1089, Universitá degli Studi di Milano.
  • Handle: RePEc:bep:unimip:unimi-1089 Note: oai:cdlib1:unimi-1089

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    References listed on IDEAS

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    3. Henrich, Joseph & Boyd, Robert & Bowles, Samuel & Camerer, Colin & Fehr, Ernst & Gintis, Herbert (ed.), 2004. "Foundations of Human Sociality: Economic Experiments and Ethnographic Evidence from Fifteen Small-Scale Societies," OUP Catalogue, Oxford University Press, number 9780199262052, June.
    4. Gary E. Bolton & Rami Zwick & Elena Katok, 1998. "Dictator game giving: Rules of fairness versus acts of kindness," International Journal of Game Theory, Springer;Game Theory Society, vol. 27(2), pages 269-299.
    5. Palfrey, Thomas R & Prisbrey, Jeffrey E, 1997. "Anomalous Behavior in Public Goods Experiments: How Much and Why?," American Economic Review, American Economic Association, vol. 87(5), pages 829-846, December.
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    causal inference; treatment effect; matching;


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