We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on … released. This is a promising machine learning application because it is a concrete prediction task for which there is a large … volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves …

We study social learning between spouses using an experiment in Chennai, India. We vary whether individuals discover … gender difference in learning (only) in the household …

Learning or experience curves are widely used to estimate cost functions in manufacturing modeling. They have recently … shows that there is a fundamental statistical identification problem in trying to separate learning from exogenous … technological change and that the estimated learning coefficient will generally be biased upwards. Second, we present two empirical …

This paper develops a theory of expectations-driven business cycles based on learning. Agents have incomplete knowledge …

, endogenous learning here eliminates that effect …

We study the perfect Bayesian equilibrium of a model of learning over a general social network. Each individual … characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social … unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some …

represent an understudied channel for this type of social learning. We study an environmentally-focused law in the shale gas …

learning between the first and the nth attempt while controlling for selection into retaking in terms of observed and … unobserved characteristics. We find large learning gains measured in terms of improvements in the exam scores, especially among …