We study the effect of releasing public information about productivity or monetary shocks when agents learn from nominal prices. While public releases have the benefit of providing new information, they can have the cost of reducing the informational efficiency of the price system. We show that,...

We study the effect of releasing public information about productivity or monetary shocks when agents learn from nominal prices. While public releases have the benefit of providing new information, they can have the cost of reducing the informational efficiency of the price system. We show that,...

Abstract We study the welfare implications of personalized pricing, an extreme form of third-degree price discrimination implemented with machine learning for a large, digital firm. We conduct a randomized controlled pricing field experiment to train a demand model and to conduct inferences...

The recent global financial crisis, the Great Recession and the subsequent implementation of a variety of unconventional policy measures have raised the issue of how to correctly measure the stance of monetary policy when policy interest rates reach the zero lower bound (ZLB). In this paper, we...

"Firm size follows Zipf's Law, a very fat-tailed distribution that implies a few large firms account for a disproportionate share of overall economic activity. This distribution of firm size is crucial for evaluating the welfare impact of economic policies such as barriers to entry or trade...

The purpose of this paper is to show how to solve linear dynamic rational expectations models with anticipated shocks by using the generalized Schur decomposition method. Furthermore, we determine the optimal unrestricted and restricted policy responses to anticipated shocks. We demonstrate our...