People update their beliefs about future outcomes in an asymmetrical manner because they incorporate new information more readily when it is desirable than undesirable. However, it has been objected that under specific circumstances optimistic belief updating can be perfectly rational according...

We study abstract macroeconomic systems in which expectations play an important role. Consistent with the recent literature on recursive learning and expectations, we replace the agents in the economy with econometricians. Unlike the recursive learning literature, however, the econometricians in...

We survey work using Bayesian learning in macroeconomics, highlighting common themes and new directions. First, we present many of the common types of learning problems agents face---signal extraction problems---and trace out their effects on macro aggregates, in different strategic settings....

This paper incorporates Bayesian estimation and optimization into portfolio selection framework, particularly for high-dimensional portfolio in which the number of assets is larger than the number of observations. We leverage a constrained 𝓁1 minimization approach, called linear programming...