We study the general problem of Bayesian persuasion (optimal information design) with continuous actions and continuous state space in arbitrary dimensions. First, we show that with a finite signal space, the optimal information design is always given by a partition. Second, we take the limit of...

Beliefs about collective outcomes, such as economic growth or firm profitability, play an important role in many contexts. We study biases in the formation of such beliefs. Specifically, we explore whether over-optimism and self-serving biases in information processing-documented for beliefs...

The impact of globalization in terms of bilateral trade is a renowned theoretical underpinning in the literature. Nevertheless, testing a trade integration model of bilateral trade is not sufficiently well estimated with the Bayesian approach to provide pragmatic evidence of trade integration...

Beliefs about collective outcomes, such as economic growth or firm profitability, play an important role in many contexts. We study biases in the formation of such beliefs. Specifically, we explore whether over-optimism and self-serving biases in information processing—documented for beliefs...

We present a general framework for Bayesian estimation and causality assessment in epidemiological models. The key to our approach is the use of sequential Monte Carlo methods to evaluate the likelihood of a generic epidemiological model. Once we have the likelihood, we specify priors and rely...

Several central banks have leaned against the wind in the housing market by increasing the policy rate preemptively to prevent a bubble. Yet the empirical literature provides mixed results on the impact of short-term interest rates on house prices: the estimated semi-elasticities range from -12...