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Model Uncertainty and Model Averaging in Regression Discontinuity Designs

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  • Button Patrick

    (Candidate, Department of Economics, University of California, Irvine, CA, USA)

Abstract

Parametric (polynomial) models are popular in research employing regression discontinuity designs and are required when data are discrete. However, researchers often choose a parametric model based on data inspection or pretesting. These approaches lead to standard errors and confidence intervals that are too small because they do not incorporate model uncertainty. I propose using Frequentist model averaging to incorporate model uncertainty into parametric models. My Monte Carlo experiments show that Frequentist model averaging leads to mean square error and coverage probability improvements over pretesting. An application to [Lee, D. S. 2008. “Randomized Experiments From Non-Random Selection in US House Elections.” Journal of Econometrics 142 (2): 675–697.] shows how this approach works in practice, and how conventionally selected models may not be ideal.

Suggested Citation

  • Button Patrick, 2016. "Model Uncertainty and Model Averaging in Regression Discontinuity Designs," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 103-116, January.
    • Handle: RePEc:bpj:jecome:v:5:y:2016:i:1:p:103-116:n:7
    DOI: 10.1515/jem-2014-0016
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    References listed on IDEAS

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    1. Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119, Decembrie.
    2. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258, September.
    3. Leeb, Hannes & Pötscher, Benedikt M., 2005. "Model Selection And Inference: Facts And Fiction," Econometric Theory, Cambridge University Press, vol. 21(1), pages 21-59, February.
    4. David S. Lee & Enrico Moretti & Matthew J. Butler, 2004. "Do Voters Affect or Elect Policies? Evidence from the U. S. House," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(3), pages 807-859.
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    Cited by:

    1. Patrick Button, 2015. "A Replication of 'Do Voters Affect or Elect Policies? Evidence from the U.S. House' (The Quarterly Journal of Economics, 2004)," Working Papers 1518, Tulane University, Department of Economics.

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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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