This dissertation examines how U.S. immigration policies, as implemented by government agents, shape migration and key employment outcomes of foreign nationals. Using unique quantitative and qualitative data, never previously available outside the U.S. Citizenship and Immigration Services (U.S. CIS) and U.S. Department of Labor (U.S. DoL), I assess agents' work legalization decisions that annually affect hundreds of thousands of workers. In so doing, I distinguish between competing theoretical accounts of labor market inequality and regulatory failure. In my first essay, I examine new U.S. CIS Freedom of Information Act data on the entire population of approved and denied H- 1B temporary work visas over a five year period. I find that immigrant workers from sending countries with lower levels of economic development are less likely to receive approvals for initial and continuing employment requests, all else equal. In support of social boundary theories, but not theories of preference-based inequality, I find no statistically significant differences in approval outcomes among those immigrants previously granted legal standing and seeking to change jobs or employers. In the second essay (co-authored with Professor Emilio J. Castilla), we examine quantitative data on the entire population of approved and denied labor certification requests, a key prerequisite for most employment-based green cards, evaluated by U.S. DoL agents over a 40 month period. We find that approvals differ significantly depending on immigrants' foreign citizenship, all else equal. Yet, and in support of statistical accounts of inequality, we find that approvals are equally likely for immigrant workers from the vast majority of citizenship groups when agents review audited applications with detailed employment information. In my final essay, I analyze qualitative data from U.S. DoL analysts charged with ensuring that the hiring of immigrant workers will not adversely affect the employment of U.S. citizens. In so doing, I explore why regulation may fail to achieve its desired outcome. In contrast to past work, I proposed that well-designed and faithfully-enacted regulation may produce inconsistent or ineffective outcomes when reliant on regulated actors' truthful accounts of their activities, resulting in "anomic regulation" that masks evaluation rules and constrains regulated actors' ability to improve compliance. 2