Tess Lallemant Do firms know what they are looking for? A Demand-Side Experiment to Reduce Labor Market Frictions Abstract: Do employer-side frictions reduce match quality in the labor market for university graduates? I conduct a randomized experiment with 376 firms posting 510 job openings in Kampala, Uganda, providing an intervention to help firms identify and communicate their hiring needs when writing job descriptions. I vary whether firms use the resulting job descriptions as public job advertisements or only for internal candidate screening, separately identifying effects through better signaling versus improved evaluation criteria. Treated firms post significantly more detailed job descriptions that attract nearly 40% larger applicant pools with better skill alignment. The intervention reduces personal network-based hiring—from 8% to essentially zero—suggesting that expanded formal applicant pools provide viable alternatives to personal connections. However, these recruitment improvements do not translate into short term better employment matches. Neither wages, employer-reported skill fit, nor performance ratings improve on average. Preliminary analysis of treatment heterogeneity suggests that organizational capacity shapes outcomes. Among firms with existing HR departments, evaluation tools improve skill match quality, while firms without HR show no such gains. The results establish that firms struggle to systematically articulate hiring requirements—a meaningful friction in developing economy labor markets—but that addressing this constraint alone is insufficient without complementary hiring infrastructure.

CSI’s Inequality Discussion Groups bring together Cornell faculty and graduate students from around campus to discuss and improve their in-progress research. Title: Government Mandates, Manager Anticipatory Compliance, and a Partisan Filter in Enforcement Expectation Abstract: Government mandates (e.g., laws, executive orders) are often initially change-prone and subject to legal contestation. Yet, some managers promptly comply despite uncertainty regarding mandate legality and scope. Less is known about the drivers of managers’ anticipatory compliance decisions. Studying this, we examine U.S. President Trump’s 2017 “Muslim ban” executive order, which sought to ban U.S. entry for immigrants from seven majority-Muslim countries. Leveraging government administrative records on employer-sponsored immigrant work authorization applications, we analyze managers’ response to the ban through anticipatory compliance (voluntary application withdrawal). Using a difference-in-differences analysis, we find withdrawal rates increased from 0.3 to 8.5 percent for immigrants from targeted majority Muslim countries in the year after the ban, relative to the year before, peaking at 29 percent. We find that this withdrawal increase is not driven by broad anti-Muslim bias, or a partisan imperative to demonstrate timely responsiveness. Rather, analyses indicate the presence of a partisan filter in enforcement expectation: Manager withdrawals from Republican-leaning employers increased gradually and peaked with the U.S. Supreme Court’s willingness to consider the Muslim Ban’s legality, which occurred in the 5-6 months after the Ban’s announcement. Findings emphasize the capacity of government to shape labor market dynamics through (even legally-contested) mandates, and the importance of accounting for employer ideology in anticipatory compliance decisions.