traditional linking methods. Second, we use the links to construct a training data set for use in supervised machine learning …

unstructured and nontraditional data like text and images, and the use of fast and flexible Machine Learning (ML) algorithms in …We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses …. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including …

conditions under which robotics and AI complement or are substituting for labor. Further, firm-level data would also allow for …-level data could be collected and used by academics, policymakers and other researchers …

disadvantages on educational outcomes. Using administrative data on the university entrance exam in Turkey we estimate cumulative … 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 …

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

, endogenous learning here eliminates that effect …

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 … model, the theoretical framework amplifies and propagates technology shocks. Improved correspondence with data arises from …

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 …