Palestinian residents of the West Bank and Gaza Strip who work in Israel generally earn more than Palestinians employed locally, but this wage premium is highly volatile. Beginning with the 1987 Palestinian uprising, changes in wage differentials by work location parallel Palestinian absences from work in Israel. This article interprets changing location differentials in response to exogenous shocks as movements along an Israeli demand curve for migrant workers. Estimates of a model of the West Bank and Gaza Strip labor market are used to evaluate the effect of policies governing Palestinian access to the Israeli labor market.

The utility of machine learning (ML) for regression-based causal inference is illustrated by using lasso to select control variables for estimates of college characteristics’ wage effects. Post-double-selection lasso offers a path to data-driven sensitivity analysis. ML also seems useful for an instrumental variables (IV) first stage, since two-stage least squares (2SLS) bias reflects overfitting. While ML-based instrument selection can improve on 2SLS, split-sample IV and limited information maximum likelihood do better. Finally, we use ML to choose IV controls. Here, ML creates artificial exclusion restrictions, generating spurious findings. On balance, ML seems ill-suited to IV applications in labor economics.

Most research on the relationship between teacher characteristics and pupil achievement focuses on salaries, experience, and education. The effect of in‐service training has received less attention. We estimate the effect of in‐service teacher training on achievement in Jerusalem elementary schools using a matched‐comparison design. Differences‐in‐differences, regression, and matching estimates suggest training in secular schools led to an improvement in test scores. The estimates for religious schools are not clear cut, perhaps because training in religious schools started later and was implemented on a smaller scale. Estimates for secular schools suggest teacher training provided a cost‐effective means of increasing test scores.

Until 1983, the language of instruction for most subjects in grades 6 and above in Moroccan public schools was French. Beginning in 1983, the language of instruction for new cohorts of Moroccan sixth graders was switched to Arabic. We use this policy change to estimate the effect of French language skills on test scores and earnings. The estimates suggest that the elimination of compulsory French instruction led to a substantial reduction in the returns to schooling for Moroccans affected by the change. This reduction appears to be largely attributable to a loss of French writing skills.

We use admissions lotteries to estimate the effects of attendance at Boston's charter high schools on college preparation, college attendance, and college choice. Charter attendance increases pass rates on the high-stakes exam required for high school graduation in Massachusetts, with especially large effects on the likelihood of qualifying for a state-sponsored college scholarship. Charter attendance has little effect on the likelihood of taking the SAT, but shifts the distribution of scores rightward, moving students into higher quartiles of the state SAT score distribution. Boston's charter high schools also increase the likelihood of taking an Advanced Placement (AP) exam, the number of AP exams taken, and scores on AP Calculus tests. Finally, charter attendance induces a substantial shift from two-to four-year institutions, though the effect on overall college enrollment is modest. The increase in four-year enrollment is concentrated among four-year public institutions in Massachusetts. The large gains generated by Boston's charter high schools are unlikely to be generated by changes in peer composition or other peer effects.