Research

This is a collection of current projects and a few older projects that I think are worthwhile making public but do not anticipate publishing.

Older Papers I Doubt I Will Ever Publish

Ability Bias, Discount Rate Bias and the Return to Education

This is a paper that I wrote a long time ago and for which I still get frequent requests. Although I got a “revise and resubmit” from a prestigious journal, I never rewrote the paper because I thought there were errors in the approach. There are definitely mistakes in the paper, but in retrospect I regret not revising it. I believe the paper was very influential in making people think about the proper interpretation of instrumental variables when coefficients are not constant and, in particular, laid some of the groundwork for the work of Josh Angrist and Guido Imbens on LATE and the work of Jim Heckman and his coauthors on the interpretation of instrumental variables. I post it here for the historical record.

The Effect of High School Exit Exams on Graduation, Employment and Incarceration (with Olesya Baker)

After a rejection, we never resubmitted this because we felt uncomfortable that the evidence for incarceration results, while intriguing and possibly important, was too limited for the attention it received. We evaluate the effects of high school exit exams on high school graduation, incarceration, employment and wages. We construct a state/graduation-cohort dataset using the Current Population Survey, Census and information on exit exams. We find relatively modest effects of high school exit exams except on incarceration. Exams assessing academic skills below the high school level have little effect. However, more challenging standards-based exams reduce graduation and increase incarceration rates. About half the reduction in graduation rates is offset by increased GED receipt. We find no consistent effects of exit exams on employment or the distribution of wages.

The Pricing of Job Characteristics When Markets Do Not Clear: Theory and Policy Implications (with Sumon Majumdar) extended version of paper in International Economic Review

There are some intriguing, at least to me, that got left out of the published version. This paper examines a model of nonsequential search when jobs can vary with respect to nonpecuniary characteristics. We find that in the presence of frictions in the labor market, the equilibrium distribution need not show evidence of compensating wage differentials. The model also generates several pervasive features of labor markets: (a) unemployment and vacancies, (b) apparent discrimination, and (c) market segmentation. When workers are homogeneous, there is no positive role for policy — restrictions on the range of job offers must decrease welfare and cannot reduce unemployment. However, when workers have heterogeneous preferences, such restrictions may lower unemployment and even lead to a Pareto-improvement in welfare. In particular, we consider the impact of policies banning discrimination and regulating working-conditions.

Current Projects

The Boss is Watching: How Monitoring Decisions Hurt Black Workers (with Costas Cavounidis and Russell Weinstein)

African Americans face shorter employment durations than similar whites. We hypothesize 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 red by previous employers after monitoring. This reduces firms’ beliefs about ability, incentivizing discriminatory monitoring. We confi rm our predictions that layoff s are initially higher for black than non-black workers but that they converge with seniority and decline more with AFQT for black workers. Two additional predictions, lower lifetime incomes and longer unemployment durations for black workers, have known empirical support.

Borrowing in an Illegal Market: Contracting with Loan Sharks (with Kaiwen Leong, Huailu Li, and Haibo Xu)

Using over 11,000 illegal loans to over 1,000 borrowers in Singapore, we provide basic information about an understudied market: illegal moneylending. Borrowers and lenders interact frequently and primarily rely 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 non nancial 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.

Estimating the Nature of Technological Change: Exploiting Shifts in Skill Use Within and Between Occupations (with Costas Cavounidis, Vittoria Dicandia, and Raghav Malhotra)

We exploit employment trends to uncover changes in skills’ productivities. Whereas Autor, Levy, and Murnane (2003) study the degree to which routine-intensity can rationalize employment trends, our reverse approach characterizes the kind of technological change that best explains shifts. We combine a tractable GE model with three DOT editions, the 1960, 1970, and 1980 Censuses, and the March CPS, to estimate changes in the relative productivities of skills. We find ‘skill bias’ – finger-dexterity productivity grew rapidly, while abstract-skill productivity lagged. With substitutability between abstract and routine inputs, these results also explain changing skill use within occupations.

The Determinants of Teachers’ Occupational Choice (with Maria Dolores Palacios)

 Among college graduates, teachers have both low average AFQT and high average risk aversion, perhaps because the compression of earnings within teaching attracts relatively risk-averse individuals. Using a dynamic optimization model with unobserved heterogeneity, we show that were it possible to make teacher compensation mimic the return to skills and riskiness of the non-teaching sector, overall compensation in teaching would increase. Moreover, this would make many current teachers substantially worse off, making reform challenging. Importantly, our conclusions are sensitive to the degree of heterogeneity for which we allow. Since even a model with no unobserved heterogeneity fits well within sample, one could easily conclude that allowing for two or three types fits the data adequately. Formal methods reject this conclusion. The BIC favors seven types. Ranking models using cross-validation, nine types is better

although the improvements of going from six to seven, from seven to eight and from eight to nine types are noticeably smaller than those from adding an additional type to a lower base.