Arguably the most aggressive affirmative action program ever implemented in the United States was a series of court-ordered racial hiring quotas imposed on municipal police departments. My best estimate of the effect of court-ordered affirmative action on work-force composition is a 14-percentage-point gain in the fraction African American among newly hired officers. Evidence on police performance is mixed. Despite substantial black-white test score differences on police department entrance examinations, city crime rates appear unaffected by litigation. However, litigation lowers slightly both arrests per crime and the fraction black among serious arrestees. (JEL H76, J15, J78, K31)

Arguably the most aggressive affirmative action program ever implemented in the United States was a series of court-ordered racial hiring quotas imposed on municipal police departments.My best estimate of the effect of court-ordered affirmative action on workforce composition is a 14 percentage point gain in the fraction African American among newly hired officers.Evidence on police performance is mixed.Despite substantial black-white test score differences on police department entrance examinations, city crime rates appear unaffected by litigation.However, litigation lowers slightly both arrests per crime and the fraction black among serious arrestees.

Using Electoral Cycles in Police Hiring to Estimate the Effect of Police on Crime: Comment by Justin McCrary. Published in volume 92, issue 4, pages 1236-1243 of American Economic Review, September 2002

Survey nonresponse and attrition undermine the validity of many and possibly most econometric estimates. We propose that survey administrators and evaluators proactively create an instrument for observation, for example, by ex ante randomizing participants to differing intensity of follow-up. We illustrate how to apply our proposed methodology using a carefully conducted randomized controlled trial, the Moving to Opportunity demonstration project, which de facto randomly assigned a subset of subjects to more intensive follow-up. The approach yields treatment effect estimates similar to the unbiased estimator based on complete administrative data and has narrower confidence intervals than alternative bounding approaches.

We review economics research regarding the effect of police, punishments, and work on crime, with a particular focus on papers from the last twenty years. Evidence in favor of deterrence effects is mixed. While there is considerable evidence that crime is responsive to police and to the existence of attractive legitimate labor-market opportunities, there is far less evidence that crime responds to the severity of criminal sanctions. We discuss fruitful directions for future work and implications for public policy. (JEL J64, K42)

Forward-looking behavior on the part of the monetary authority makes it difficult to estimate the effect of monetary policy interventions on output. We present instrumental variables estimates of the impact of interest rates on quarterly real output for several European countries, using German interest rates as the instrument. These estimates confirm a strong forward-looking bias in least squares estimates that persists even conditional on standard controls for the history of the system. Due to the potential for correlation of output shocks across countries, we interpret our estimates as lower bounds for the effect of monetary policy on real output.

We document the extent of measurement errors in the basic data set on police used in the literature on the effect of police on crime. Analyzing medium to large U.S. cities over 1960 to 2010, we obtain measurement error-corrected estimates of the police elasticity. The magnitudes of our estimates are similar to those obtained in the quasi-experimental literature, but our approach yields much greater parameter certainty for the most costly crimes, the key parameters for welfare analysis. Our analysis suggests that U.S. cities are substantially underpoliced.

This paper uses age-at-school-entry policies to identify the effect of female education on fertility and infant health. We focus on sharp contrasts in schooling, fertility, and infant health between women born just before and after the school entry date. School entry policies affect female education and the quality of a woman's mate and have generally small, but possibly heterogeneous, effects on fertility and infant health. We argue that school entry policies manipulate primarily the education of young women at risk of dropping out of school.

Frölich (2004) compares the finite sample properties of reweighting and matching estimators of average treatment effects and concludes that reweighting performs far worse than even the simplest matching estimator. We argue that this conclusion is unjustified. Neither approach dominates the other uniformly across data-generating processes (DGPs). Expanding on Frölich's analysis, this paper analyzes empirical as well as hypothetical DGPs and also examines the effect of misspecification. We conclude that reweighting is competitive with the most effective matching estimators when overlap is good, but that matching may be more effective when overlap is sufficiently poor.

This paper investigates fractional share trading. We develop a latency-based method for identifying a large sample of fractional share trades. We find that high-priced stocks, meme stocks, IPOs, SPACs, and popular retail stocks exhibit considerable numbers of these tiny trades. We surmise that this reflects dollar-based order entry, with many tiny trades being fractional components of larger orders. We show that our fractional trade measure is predictive of future liquidity and volatility, suggesting a new metric to capture the information in retail trades. We identify how data and reporting protocols preclude knowing the extent of fractional share trading, inflate volume data, and provide censured samples of these off-exchange trades.