We present evidence that more ethnically fragmented communities spend, all else equal, more on police services than less fragmented communities. We introduce a model of spending on police services which we use to interpret the data. In this model, we assume that the decision to commit a crime is...

This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honor'e and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that...

This paper introduces a exible local projection that generalises the model by Jordà (2005) to a non-parametric setting using Bayesian Additive Regression Trees. Monte Carlo experiments show that our BART-LP model is able to capture non-linearities in the impulse responses. Our first application...

We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural...

Vector autoregressions (VARs) are economically interpretable only when identified by being transformed into a structural form (the SVAR) in which the contemporaneous variables stand in a well-defined causal order. These identifying transformations are not unique. It is widely believed that...

Labor market programs may affect unemployed individuals' behavior before they enroll. Such ex ante effects are hard to identify without model assumptions. We develop a novel method that relates self-reported perceived treatment rates and job-search behavioral outcomes, like the reservation wage,...