We discuss the relevance of the recent machine learning (ML) literature for economics and
econometrics. First we discuss the differences in goals, methods, and settings between the …

Electronic health records (EHRs) adoption has become nearly universal during the past
decade. Academic research into the effects of EHRs has examined factors influencing …

We study the effects of industrial robots on US labor markets. We show theoretically that
robots may reduce employment and wages and that their local impacts can be estimated …

In this paper, we discuss recent developments in econometrics that we view as important for
empirical researchers working on policy evaluation questions. We focus on three main …

Can machine learning improve human decision making? Bail decisions provide a good test
case. Millions of times each year, judges make jail-or-release decisions that hinge on a …

We study the effect of physician workforce diversity on the demand for preventive care
among African American men. In an experiment in Oakland, California, we randomize black …

This paper provides an assessment of the early contributions of machine learning to
economics, as well as predictions about its future contributions. It begins by briefly …

" Now in its fourth edition, this comprehensive introduction to fundamental panel data
methodologies provides insights on what is most essential in panel literature. A capstone to …

We propose a model selection method to systematically evaluate the contribution to asset
pricing of any new factor, above and beyond what a high‐dimensional set of existing factors …

The synthetic control method (SCM) is a popular approach for estimating the impact of a
treatment on a single unit in panel data settings. The “synthetic control” is a weighted …