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A Quartet of Semigroups for Model Specification, Robustness, Prices of Risk, and Model Detection

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Author Info
Evan W. Anderson (University of North Carolina,)
Lars Peter Hansen (University of Chicago,)
Thomas J. Sargent (New York University and Hoover Institution,)

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Abstract

A representative agent fears that his model, a continuous time Markov process with jump and diffusion components, is misspecified and therefore uses robust control theory to make decisions. Under the decision maker's approximating model, cautious behavior puts adjustments for model misspecification into market prices for risk factors. We use a statistical theory of detection to quantify how much model misspecification the decision maker should fear, given his historical data record. A semigroup is a collection of objects connected by something like the law of iterated expectations. The law of iterated expectations defines the semigroup for a Markov process, while similar laws define other semigroups. Related semigroups describe (1) an approximating model; (2) a model misspecification adjustment to the continuation value in the decision maker's Bellman equation; (3) asset prices; and (4) the behavior of the model detection statistics that we use to calibrate how much robustness the decision maker prefers. Semigroups 2, 3, and 4 establish a tight link between the market price of uncertainty and a bound on the error in statistically discriminating between an approximating and a worst case model. (JEL: C00, D51, D81, E1, G12) Copyright (c) 2003 The European Economic Association.

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Article provided by MIT Press in its journal Journal of the European Economic Association.

Volume (Year): 1 (2003)
Issue (Month): 1 (03)
Pages: 68-123
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Handle: RePEc:tpr:jeurec:v:1:y:2003:i:1:p:68-123

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