Global warming, sea level rise, and extreme weather events have made climate change a top priority for policymakers across the globe. But which policies are best suited to tackle the enormous challenges presented by our changing climate? This Article proposes that policymakers turn to prediction...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Temporal climate risk weighs heavily on many of the world's poor. Model-based climate forecasts could benefit such populations, provided recipients use forecast information to update climate expectations. We test whether pastoralists in southern Ethiopia and northern Kenya update their...

This note shows that combining external forecasts such as the Survey of Professional Fore casters can significantly increase DSGE forecast accuracy while preserving the interpretability in terms of structural shocks. Applied to pseudo real-time from 1997q2 onward, the canonical Smets and Wouters...

In an environment that features second-degree price discrimination, this paper fully characterizes the set of surplus divisions that can arise from all possible information consumers have about their valuation. By extending the techniques developed in a companion paper (Yang, 2019a), I show that...