Ambiguity and Robustness in Macroeconomics and Finance

February 15–16, 2013

(All day)

Charles M. Harper Center
Jaroslav Borovička, New York University
Lars Peter Hansen, University of Chicago
Cosmin Ilut, Duke University
Thomas J. Sargent, New York University

The Becker Friedman Institute for Research in Economics brought together scholars from around the world to tackle the subject of ambiguity—a cutting-edge topic in economics and a key issue in attempting to understand asset prices and the dynamics of individual responses to risk and uncertainty over time.

Developing Ways to Model Complexity


Ambiguity is a special feature of economic modeling. In traditional models, agents do not know the outcome of a process in advance, but they almost always know the rules of the world they live in, so they know the probabilities of each possible outcome. In reality, economic decision makers often face a complex environment where it is challenging to assess the probabilities of profit or loss. They may have doubts about their own assumptions about the rules governing their world and guiding their decisions. They may know the truth lies in a class of models, but do not have enough information to weight the relevance and accuracy of each model.

Representing these sources of ambiguity in economic modeling in tractable ways can be highly revealing. This conference brought together experts in decision theory with researchers from macroeconomics and finance to explore alternative conceptual approaches and their practical use. The event specifically highlighted the work of young researchers. New work at this conference addressed a range of important questions:

  • How does aversion to ambiguity alter the observed counterpart to what is typically viewed as a risk-return relationship and dividend price ratios?
  • How do investor struggles with uncertainty alter the pricing of sovereign debt when default is a possibility?
  • How should policymaking be altered when a government has limited data and knowledge about an underlying economy under alternative policy scenarios?

Ambiguity, Asset Pricing, and Policy Uncertainty

The conference saw two distinct strains of research topics: the first involved ambiguity in the context of asset pricing. Yehuda Izhakian kicked off the conference's first day with his paper on this particular topic. He examined how standard asset pricing concepts such as portfolio theory and the tradeoff between mean asset return and asset volatility might be extended to include ambiguity.

The second strain of research touched on how policy-making agents such as individuals or governments act when they have uncertainty about the model that describes the world they live in.

The conference also highlighted different treatments of how agents feel about ambiguity. Some papers used preferences displaying extreme levels of ambiguity aversion. These papers assume that agents have a set of possible worlds in mind, assume the worst, and choose their behaviors to minimize their maximum expected loss. These agents choose the most robust decision available.

Other papers specifically represented agents who are averse to ambiguity but are willing to make explicit tradeoffs between different possibilities. For example, an agent may not know whether or not long-run growth has shifted down permanently after a crisis, but might not be willing to assume the worst case scenario will occur with certainty.

Models presented also differed in their measures of ambiguity. Some papers explicitly advanced models of uncertainty that allowed them to back out measures of ambiguity, while others showed that models with varying degrees of ambiguity could replicate observable data.

Poster Session Widens Discussion


The first day of the conference included a poster session in which eight papers were presented by authors in an informal setting. Topics ranged from how ambiguity might impact people's self-insurance and savings to how lenders in a world of ambiguity may generate countercyclical interest rates in emerging economies. Others focused on how we might insert ambiguity into standard macroeconomic methods, such as dynamic stochastic general equilibrium (DSGE) models.

During the conference, coorganizer Thomas J. Sargent put forward a challenge for future work in ambiguity. He noted that many calculations of optimal government policy depend on what people believe the government policy would have been in different states of the world that may not come to pass. For example, the threat of nuclear annihilation if war occurs may make the use of nuclear weapons unnecessary, leading to peace in equilibrium.

Many economic models depend on agents knowing these "off-equilibrium threats" with certainty. Pointing to monetary policy, Sargent proposed that when governments or agents are uncertain about off-equilibrium threats, many of these optimal policies may change dramatically. Sargent's suggestion was one of many new directions for ambiguity research discussed during the conference.

The first day of the conference featured poster sessions highlighting additional work.


The Institute gratefully acknowledges generous funding for this conference from Donald R. Wilson Jr., AB'88, and Edward R. Allen, PhD'92.

February 15, 2013 (All day) February 16, 2013 (All day)