Racism. Sexism. Heterosexism. Gender binarism. Together, they comprise intimately
harmful, distinct, and entangled societal systems of self-serving domination and privilege …

External validity captures the extent to which inferences drawn from a given study's sample
apply to a broader population or other target populations. Social scientists frequently invoke …

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 …

We apply causal forests to a dataset derived from the National Study of Learning Mindsets,
and discusses resulting practical and conceptual challenges. This note will appear in an …

Flexible estimation of heterogeneous treatment effects lies at the heart of many statistical
applications, such as personalized medicine and optimal resource allocation. In this article …

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 …

An innovative and accessible guide to doing social research in the digital age. In just the
past several years, we have witnessed the birth and rapid spread of social media, mobile …

This work considers the question of how convenient access to copious data impacts our
ability to learn causal effects and relations. In what ways is learning causality in the era of …

We revisit the classic semi‐parametric problem of inference on a low‐dimensional
parameter θ0 in the presence of high‐dimensional nuisance parameters η0. We depart from …

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 …