Abstract
This dissertation examines how policy interventions in the labor market shape worker outcomes. Across three chapters, I study three distinct policy levers: direct income support paired with job training, design choices within cash-plus programs, and information rules governing salary negotiation. I evaluate their effects on employment, earnings, economic security, and broader measures of worker welfare. Each chapter combines applied microeconomics methods with policy-relevant data to estimate how specific institutional features shape labor market outcomes for the populations they affect.
The first chapter presents experimental evidence from a three-year randomized evaluation of the TAYportunity + Guaranteed Income (TAYGI) program in Los Angeles County, which provided economically vulnerable young adults with $1,000 per month for 36 months alongside access to a structured job training program. Using six waves of survey data and administrative arrest records, I find substantial improvements across labor market and well-being outcomes: employment rises by 7 percentage points, monthly earnings by roughly 30 percent, and felony arrests fall by 40 percent. Instrumental variables estimates exploiting random assignment to caseworkers indicate that the job-training component, conditional on cash, accounts for much of the program's overall impact.
The second chapter situates the TAYGI evidence within the broader literatures on cash transfers and active labor-market programs. I assemble comparative evidence across more than a dozen studies and use TAYGI's dynamic and heterogeneous treatment effect estimates to address two design questions the existing literature has not directly answered: how long cash-plus programs need to run, and which populations they should prioritize. The combined evidence supports a set of design recommendations grounded in patterns documented across multiple independent studies.
The third chapter turns from direct income support to information-based interventions, examining the effects of salary history bans and wage transparency laws on worker outcomes in the U.S. labor market. I develop a model showing how reducing asymmetric wage information between workers and firms can raise equilibrium wages, and use an event-study design with American Community Survey data from 2010–2021 to show that pay information equity laws have led to higher mean wages and greater wage dispersion in states where they have been enacted.
Together, the three chapters contribute to a growing literature on how active policy levers: income, skill investment, and information, shape labor-market outcomes for workers across a range of contexts. The findings suggest that the design and combination of these levers can meaningfully affect worker welfare and that empirical evaluation of specific policy choices is essential to understanding their effects.
