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kmatch: Kernel matching with automatic bandwidth selection

Author

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  • Ben Jann

    (Institute of Sociology, University of Bern)

Abstract

In this talk I will present a new matching software for Stata called kmatch. The command matches treated and untreated observations with respect to covariates and, if outcome variables are provided, estimates treatment effects based on the matched observations, optionally including regression adjustment bias-correction. Multivariate (Mahalanobis) distance matching as well as propensity score matching is supported, either using kernel matching, ridge matching, or nearest-neighbor matching. For kernel and ridge matching, several methods for data-driven bandwidth selection such as cross-validation are offered. The package also includes various commands for evaluating balancing and common-support violations. A focus of the talk will be on how kernel and ridge matching with automatic bandwidth selection compare to nearest-neighbor matching.

Suggested Citation

  • Ben Jann, 2017. "kmatch: Kernel matching with automatic bandwidth selection," United Kingdom Stata Users' Group Meetings 2017 11, Stata Users Group.
    • Handle: RePEc:boc:usug17:11
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    Cited by:

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    7. Mingming Xu & Benjamin Bittschi, 2022. "Does the abolition of copayment increase ambulatory care utilization?: a quasi-experimental study in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(8), pages 1319-1328, November.
    8. Hagendorff, Jens & Nguyen, Duc Duy & Sila, Vathunyoo, 2022. "Does marriage equality promote credit access? Evidence from same-sex marriage laws," Journal of Corporate Finance, Elsevier, vol. 77(C).
    9. Dai, Xiaoyong & Chapman, Gary, 2022. "R&D tax incentives and innovation: Examining the role of programme design in China," Technovation, Elsevier, vol. 113(C).

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