Knowledge that Transforms

We consider a dynamic monetary economy where agents gradually learn about the holding cost of a new asset and coordinate to adopt it as money or abandon it. We provide closed-form solutions for state-contingent asset prices and agents’ adoption decision. The transactional benefits of using money are endogenous and can convexify or concavify the payoff structure. Thus, the arrival of new information can raise or reduce the asset’s price, which is in sharp contrast to standard insights in experimentation models. Full disclosure of the asset type and an increase in the learning speed improve information but have different welfare implications.

What is the optimal fiscal policy response to a recession when the government is subject to sovereign risk? We study this question in a model of endogenous sovereign default with nominal rigidities. Increasing spending in a recession reduces unemployment, but it exposes the government to a debt crisis. We quantitatively analyze this trade-off between stimulus and austerity and find that expanding government spending may be undesirable, even in the presence of sizable Keynesian stabilization gains and inequality concerns. Consistent with these findings, we show that sovereign risk is a key driver of the fiscal procyclicality observed worldwide.

This paper studies the optimal determination of deposit insurance when bank runs are possible. We show that the welfare impact of changes in the level of deposit insurance coverage can be generally expressed in terms of a small number of sufficient statistics, which include the level of losses in specific scenarios and the probability of bank failure. We characterize the wedges that determine the optimal ex ante regulation, which map to asset- and liability-side regulation. We demonstrate how to employ our framework in an application to the most recent change in coverage in the United States, which took place in 2008.

This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple measurement of cognitive uncertainty generates novel insights about what people find complex and how they respond to it.