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)

Abstract 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 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.