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 …

Asset pricing theory has long recognized that financial markets compensate investors who
are exposed to some components of uncertainty. This is where macroeconomics comes into …

From an econometric standpoint, the outcome of the rational expectations approach is the
availability of extra information about the underlying economic model. This information is …

Climate change and uncertainty about its potential consequences has become a central
concern for economists, investors, and policymakers alike. I use a stochastic, dynamic …

This paper develops a method informed by data and models to recover information about
investor beliefs. Our approach uses information embedded in forward-looking asset prices in …

We examine how policymakers react to a pandemic with uncertainty around key
epidemiological and economic policy parameters by embedding a macroeconomic SIR …

We use statistical detection theory in a continuous-time environment to provide a new
perspective on calibrating a concern about robustness or an aversion to ambiguity. A …

Investors face uncertainty over models when they do not know which member of a set of well-
defined “structured models” is best. They face uncertainty about models when they suspect …

In this paper, we introduce a novel framework that allows efficient stochastic process
discrimination. The underlying test statistic is based on even empirical moments and …

Written by Lars Peter Hansen (Nobel Laureate in Economics, 2013) and Thomas Sargent
(Nobel Laureate in Economics, 2011), Uncertainty within Economic Models includes articles …