Machine learning algorithms can find predictive signals that researchers fail to notice; yet they are notoriously hard-to-interpret. How can we extract theoretical insights from these black boxes? History provides a clue. Facing a similar problem - how to extract theoretical insights from their...

We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed...

Economic policies often involve dynamic interventions, where individuals receive repeated interventions over multiple periods. This dynamics makes past responses informative to predict future responses and ultimate outcomes depend on the history of interventions. Despite these phenomena,...

In a pilot program during the 2016-17 admissions cycle, the University of California, Berkeley invited many applicants for freshman admission to submit letters of recommendation. This proved controversial within the university, with concerns that this change would further disadvantage applicants...

The United Nations Human Development Index (HDI) is arguably the most widely used alternative to gross domestic product for measuring national development. This is in large part due to its multidimensional nature, as it incorporates not only income, but also education and health. However, the...

Many of the challenges in the estimation of dynamic heterogeneous treatment effects can be resolved with local projection (LP) estimators of the sort used in applied macroeconometrics. This approach provides a convenient alternative to the more complicated solutions proposed in the recent...

The extant literature predicts market returns with "simple" models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to "complex" models in which the number of parameters exceeds the...

This article describes methods used in the field of spatial economics that combine insights from economic theory and evidence from data in order to answer counter- factual questions. I outline a general framework that emphasizes three elements: a specific question to be answered, a set of...

We develop a new class of tree-based models (P-Tree) for analyzing (unbalanced) panel data utilizing global (instead of local) split criteria that incorporate economic guidance to guard against overfitting while preserving interpretability. We grow a P-Tree top-down to split the cross section of...

A key contention in economics is the discrepancy between micro and macro elasticities of labor supply with respect to marginal tax rates. We revisit this question, focusing on the role of dynamic returns to effort among top earners. We develop a new model of earnings responses to taxes in the...