Uncertainty within Economic Models by Lars Peter Hansen, Thomas J Sargent

By Lars Peter Hansen, Thomas J Sargent

Uncertainty inside fiscal versions is a suite of papers adapting and using strong keep an eye on conception to difficulties in economics and finance. This booklet extends rational expectancies versions through together with brokers who doubt their versions and undertake precautionary judgements designed to guard themselves from adversarial results of version misspecification. This habit has results for what are more often than not interpreted as marketplace costs of chance, yet massive elements of which should still really be interpreted as industry costs of version uncertainty. The chapters talk about methods of calibrating brokers' fears of version misspecification in quantitative contexts.

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All chapters in this book generate this set in the special way described above. First, we impute to the decision maker a single model that we refer to at different times either as his approximating model or his benchmark model. 1. Questions about Model Uncertainty b1808-ch01 page 5 5 it with a continuum of probability models that lie within a ball determined by entropy relative to the approximating model. That procedure gives the decision maker a vast set of models whose proximities to the approximating model are judged by their relative entropies.

A semigroup is a collection of objects that satisfies conditions activating the law of iterated expectations, a workhorse familiar both to econometricians and to rational expectations theorists. These same conditions underly a law of iterated values widely used in pricing assets of different maturities. The four semigroups featured in this chapter pertain to (1) a Markov process that we interpret as a decision maker’s benchmark probability model; (2) a perturbation to that benchmark model that we use to express an alternative specification that a decision maker or representative consumer fears might actually govern the data; (3) a stochastic discount factor that assigns prices to risks that a benchmark Markov statistical model presents to a representative consumer; and (4) a stochastic process that generates bounds on errors in a good statistical test for discriminating between a benchmark model and a perturbation to it.

When some agents inside an equilibrium model themselves use multiple models to express their uncertainty, we need some device to replace that rational expectations communism. In Chapter 11, we assume that all agents share a common benchmark or approximating model, but allow them to have differing degrees of doubt about the benchmark model. Chapter 11 discusses the consequences of three types of doubt that a Ramsey planner might have about a benchmark model. 13 13 Ramsey problems with a different type of ambiguity are analyzed by Karantounias (2013) and Orlik and Presno (2012).

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