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Why ask Why? Forward Causal Inference and Reverse Causal Questions

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  • Andrew Gelman
  • Guido Imbens

Abstract

The statistical and econometrics literature on causality is more focused on "effects of causes" than on "causes of effects." That is, in the standard approach it is natural to study the effect of a treatment, but it is not in general possible to define the causes of any particular outcome. This has led some researchers to dismiss the search for causes as "cocktail party chatter" that is outside the realm of science. We argue here that the search for causes can be understood within traditional statistical frameworks as a part of model checking and hypothesis generation. We argue that it can make sense to ask questions about the causes of effects, but the answers to these questions will be in terms of effects of causes.

Suggested Citation

  • Andrew Gelman & Guido Imbens, 2013. "Why ask Why? Forward Causal Inference and Reverse Causal Questions," NBER Working Papers 19614, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:19614
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    References listed on IDEAS

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    1. Cartwright,Nancy, 2007. "Hunting Causes and Using Them," Cambridge Books, Cambridge University Press, number 9780521860819.
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    3. Levitt, Steven D, 1994. "Using Repeat Challengers to Estimate the Effect of Campaign Spending on Election Outcomes in the U.S. House," Journal of Political Economy, University of Chicago Press, vol. 102(4), pages 777-798, August.
    4. Teppei Yamamoto, 2012. "Understanding the Past: Statistical Analysis of Causal Attribution," American Journal of Political Science, John Wiley & Sons, vol. 56(1), pages 237-256, January.
    5. Cartwright,Nancy, 2007. "Hunting Causes and Using Them," Cambridge Books, Cambridge University Press, number 9780521677981.
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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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