Risk, Ambiguity, and Misspecification: Decision Theory, Robust Control, and Statistics

29 Pages Posted: 29 Nov 2022

See all articles by Lars Peter Hansen

Lars Peter Hansen

University of Chicago - Department of Economics; National Bureau of Economic Research (NBER)

Thomas J. Sargent

New York University (NYU) - Department of Economics, Leonard N. Stern School of Business; National Bureau of Economic Research (NBER)

Date Written: November 28, 2022

Abstract

We connect variational preferences with the likelihood functions and prior probabilities over parameters that are building blocks of statistics and econometrics. We use relative entropy and other statistical divergences as cost functions in the variational preferences of someone who is ambiguous in the sense of not having a unique prior over a discrete set or manifold of statistical models (i.e., likelihood functions) and who suspects that each statistical model is misspecified. We connect variational preferences to theories of robust control and statistical approximation.

Keywords: Variational preferences, statistical divergence, relative entropy, prior, likelihood, ambiguity, misspecification

JEL Classification: C10,C14,C18

Suggested Citation

Hansen, Lars Peter and Sargent, Thomas J., Risk, Ambiguity, and Misspecification: Decision Theory, Robust Control, and Statistics (November 28, 2022). University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2022-157, Available at SSRN: https://ssrn.com/abstract=4287610 or http://dx.doi.org/10.2139/ssrn.4287610

Lars Peter Hansen (Contact Author)

University of Chicago - Department of Economics ( email )

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Thomas J. Sargent

New York University (NYU) - Department of Economics, Leonard N. Stern School of Business ( email )

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United States
212-998-3548 (Phone)

National Bureau of Economic Research (NBER)

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United States

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