Robust Control and Model Uncertainty

Empirical work in macroeconomics and finance typically assumes a unique and explicitly specified dynamic statistical model. To use Gilboa and Schmeidler's (1989) multiple-model expected utility theory, the paper turns to robust-control theory for a parsimonious set of alternative models with ri...

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Bibliographic Details
Published in:The American economic review 2001-05, Vol.91 (2), p.60-66
Main Authors: Hansen, Lars Peter, Sargent, Thomas J.
Format: Article
Language:English
Subjects:
Brownian motion
Control theory
Decision analysis
Decision making
Decision making models
Decision theory
Economic shock
Economic theory
Entropy
Expected utility
Lagrange multipliers
Macroeconomics
Parametric models
Probability distributions
Resource allocation
Risk aversion
Robustness to Uncertainty
State vectors
Stochastic processes
Studies
Uncertainty
Utility theory
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Summary:Empirical work in macroeconomics and finance typically assumes a unique and explicitly specified dynamic statistical model. To use Gilboa and Schmeidler's (1989) multiple-model expected utility theory, the paper turns to robust-control theory for a parsimonious set of alternative models with rich alternative dynamics. Those alternative models come from perturbing the decision-maker's approximating model to allow its shocks to feed back on state variables arbitrarily. This allows the approximating model to miss functional forms, the serial correlation of shocks and exogenous variables, and how those exogenous variables impinge on endogenous state variables.
ISSN:0002-8282
1944-7981
DOI:10.1257/aer.91.2.60