We study a robo-advising framework that allows for interactions with a client who has time-varying risk preferences that can be mismeasured. A client's willingness to interact is incorporate using a budget constraint. We find that when measurements are more volatile interacting frequently can...

We conduct an experiment with a representative sample from the US to study households' demand for macroeconomic information. Respondents who learn of a higher personal exposure to unemployment risk during recessions increase their demand for an expert forecast about the likelihood of a...

We conduct an experiment with a representative sample from the US to study households’ demand for macroeconomic information. Respondents who learn of a higher personal exposure to unemployment risk during recessions increase their demand for an expert forecast about the likelihood of a...

A representative consumer uses Bayes' law to learn about parameters of several models and to construct probabilities with which to perform ongoing model averaging. The arrival of signals induces the consumer to alter his posterior distribution over models and parameters. The consumer's...

Using a news-based gauge of geopolitical risk, we study its role for asset pricing in global emerging markets. We find that changes in risk positively predict future stock returns. The countries with the highest increase in geopolitical uncertainty outperform their counterparts with the lowest...

We study an economy with incomplete information in which two agents are uncertain and disagree about the length of business cycles. That is, the agents do not question whether the economy is growing or not, but instead continuously estimate how long economic cycles will last — i.e., they learn...

This paper documents that when a southern California home gets designated to a wildfire risk zone, its price drops by 11% relative to homes just outside the designation boundary. Whereas the risk designation is discontinuous, the underlying risk is continuous — suggesting the price effect is...

We show theoretically that when Bayesian investors face time-series uncertainty about assets' risk exposures, differences in their priors affect the pricing of risk in the cross-section: different priors for the same asset can generate differences in perceived risk exposures, and thereby...

We examine the effects of estimation risk and Bayesian learning on equilibrium asset prices when there is uncertainty about both the first and second moments of consumption and dividend growth rates. For the 1891-2007 period, our model generates a sizable average annual equity premium,...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...