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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.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 19614.

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Date of creation: Nov 2013
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Handle: RePEc:nbr:nberwo:19614

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  1. Ashraf, Quamrul & Galor, Oded, 2012. "The "Out of Africa" Hypothesis, Human Genetic Diversity, and Comparative Economic Development," IZA Discussion Papers 6330, Institute for the Study of Labor (IZA).
  2. 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 777-98, August.
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Cited by:
  1. Huber, Martin & Mellace, Giovanni & Lechner, Michael, 2014. "The finite sample performance of estimators for mediation analysis under sequential conditional independence," Economics Working Paper Series 1415, University of St. Gallen, School of Economics and Political Science.

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