Kevin Lang

Using over 11,000 unlicensed loans to over 1,000 borrowers in Singapore, we provide basic information about an understudied market: illegal moneylending. Borrowers and lenders interact frequently and rely primarily on relational contracts to enforce their agreements. Borrowers have high discount rates, often have gambling and/or substance abuse problems, and often repay late. While lenders sometimes resort to nonfinancial punishments, the primary cost of late repayment is the compounding of a very high interest rate. Consistent with our view that lenders cannot extract all surplus, a crackdown on illegal lending raised interest rates and lowered the size of loans.

We present a unified technological explanation of both the movement of workers across jobs using different skills and the changes in skill use within jobs. An envelope-theorem approach allows us to estimate relative skill-productivity growth from worker mobility using OLS while making minimal assumptions on each occupation's production function. Using six decades of data, we conclude that routine-cognitive- and finger-dexterity-skill productivity grew rapidly and abstract- and social-skill productivity grew slowly - a form of "skill bias." These effects, along with our estimated relationships between skill inputs, also explain changes in skill use within occupations.

African Americans face shorter employment durations than similar Whites. We hypothesise that employers discriminate in acquiring or acting on ability-relevant information. In our model, monitoring Black, but not White, workers is self-sustaining. New Black hires were more likely fired by previous employers after monitoring. This reduces firms’ beliefs about ability, incentivising discriminatory monitoring. We confirm our predictions that layoffs are initially higher for Black than non-Black workers, but that they converge with seniority and decline more with the Armed Forces Qualification Test for Black workers. Two additional predictions, lower lifetime incomes and longer unemployment durations for Black workers, have known empirical support.

We review the empirical literature in economics on discrimination in the labor market and criminal justice system, focusing primarily on discrimination by race. We then discuss theoretical models of taste-based discrimination, particularly models of frictional labor markets and models of statistical discrimination, including recent work on invalid statistical discrimination. We explore and evaluate the evidence for and against these theories. Although there is substantial evidence of the existence of discrimination, little is known about the extent to which disparities are driven by discrimination. Finally, we argue that economists miss the important self-enforcing relationship between disparities and discrimination and the effect of disparities in one domain on discrimination in other domains.

We use the exchange between Kearney/Levine and Jaeger/Joyce/Kaestner on 16 and Pregnant to reexamine the use of DiD as a response to the failure of nature to properly design an experiment for us. We argue that (1) any DiD paper should address why the original levels of the experimental and control groups differed, and why this would not impact trends, (2) the parallel trends argument requires a justification of the chosen functional form and that the use of the interaction coefficients in probit and logit may be justified in some cases, and (3) parallel trends in the period prior to treatment is suggestive of counterfactual parallel trends, but parallel pre-trends is neither necessary nor sufficient for the parallel counterfactual trends condition to hold. Importantly, the purely statistical approach uses pretesting and thus, generates the wrong standard errors. Moreover, we underline the dangers of implicitly or explicitly accepting the null hypothesis when failing to reject the absence of a differential pre-trend.

We measure the black–white achievement gap from kindergarten through seventh grade on an interval scale created by tying each grade–test score combination to average eventual education. After correcting for various sources of test measurement error, some of which are unique to forward-looking scales, we find no racial component in the evolution of the achievement gap through the first eight years of schooling. Further, most, if not all, of the gap can be explained by socioeconomic differences. Our results suggest that the rising racial test gap in previous studies probably reflects excessive measurement error in testing in the early grades.