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What Now? Some Brief Reflections on Model-Free Data Analysis

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  • Richard Berk

    (University of Pennsylvania)

Abstract

David Freedman’s critique of causal modeling in the social and biomedical sciences was fundamental. In his view, the enterprise was misguided, and there was no technical fix. Far too often, there was a disconnect between what the statistical methods required and the substantive information that could be brought to bear. In this paper, I briefly consider some alternatives to causal modeling assuming that David Freedman’s perspective on modeling is correct. In addition to randomized experiments and strong quasi-experiments, I discuss multivariate statistical analysis, exploratory data analysis, dynamic graphics, machine learning and knowledge discovery.

Suggested Citation

  • Richard Berk, 2009. "What Now? Some Brief Reflections on Model-Free Data Analysis," International Econometric Review (IER), Econometric Research Association, vol. 1(1), pages 18-27, April.
    • Handle: RePEc:erh:journl:v:1:y:2009:i:1:p:18-27
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    References listed on IDEAS

    as
    1. 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.
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    3. Kenneth W. Wachter & David A. Freedman, 2000. "Measuring Local Heterogeneity with 1990 U.S. Census Data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 3(10).
    4. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
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    6. Leeb, Hannes & Pötscher, Benedikt M., 2008. "Can One Estimate The Unconditional Distribution Of Post-Model-Selection Estimators?," Econometric Theory, Cambridge University Press, vol. 24(2), pages 338-376, April.
    7. Klaus Nordhausen, 2009. "The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition by Trevor Hastie, Robert Tibshirani, Jerome Friedman," International Statistical Review, International Statistical Institute, vol. 77(3), pages 482-482, December.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Causal Modeling; Regression Analysis; Exploratory Data Analysis; Data Science;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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