Prediction Policy Problems

Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan and Ziad Obermeyer

American Economic Review, 2015, vol. 105, issue 5, 491-95

Abstract: Most empirical policy work focuses on causal inference. We argue an important class of policy problems does not require causal inference but instead requires predictive inference. Solving these "prediction policy problems" requires more than simple regression techniques, since these are tuned to generating unbiased estimates of coefficients rather than minimizing prediction error. We argue that new developments in the field of "machine learning" are particularly useful for addressing these prediction problems. We use an example from health policy to illustrate the large potential social welfare gains from improved prediction.

JEL-codes: C50 C53 D83 (search for similar items in EconPapers)
Date: 2015
Note: DOI: 10.1257/aer.p20151023
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Citations: View citations in EconPapers (184)

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