Abstract. This paper studies how wealth affects workers’ ability to move to higher-paying jobs. Using microdata from the SIPP, I compare similar workers and find that those with higher liquid wealth are 35\% more likely to change jobs than workers with no savings. To explain this pattern, I develop a job ladder model with incomplete markets, risk-averse workers, and wage posting, where firms learn about match quality over time. Because firms gradually screen out workers in bad matches, changing jobs restarts the learning process and raises the risk of job loss. Workers with no liquidity, unable to insure against unemployment risk, prioritize job security over job mobility and remain trapped in low-paying jobs. This mechanism accounts for nearly 60\% of the observed wealth gap in job mobility, and shutting it down yields both higher aggregate mobility and lower income inequality. More generous unemployment insurance offers a pathway out of the job trap: the optimal policy is hump-shaped in income and extends benefit duration to two years, raising welfare by over 5\% while reducing inequality at no additional fiscal cost.
Awards: Econ JM Best Paper Award by EEA and UniCredit , AEA Summer Economics Fellowship, GSAS Dissertation Fellowship, Summer Dissertation Fellowship
Federal Reserve Bank of Philadelphia, Dallas Fed Women in Central Banking Workshop, Search and Matching (SaM) annual conference, Midwest Macro, CSWEP session at WEAI, CEBRA annual meeting, Federal Reserve Bank of Kansas City, Green Line Macro Meeting, Boston College, Aarhus Workshop on Labor Economics, Southern Economics Association Annual Meeting
Abstract. We provide new evidence on the drivers of assortative marriage in the United States. Using four decades of microdata from the American Community Survey, we document substantial spatial variation in assortative mating over income: it is strongest in areas with higher housing costs and a larger share of college-educated workers. To interpret these patterns, we develop a spatial marriage-market model that embeds a search-and-matching framework within a superstar-city environment, characterized by heterogeneous housing supply elasticities and returns to productivity. The model replicates observed wage and housing price differentials across cities and generates spatial and marital sorting patterns consistent with the data. In equilibrium, skilled workers endogenously sort into more productive, high-cost cities, where they are more likely to meet and marry other high earners. Preliminary quantitative results suggest that assortative mating on income is substantially stronger in superstar cities than in the average metropolitan area.
Boston College Applied Micro Brownbag Seminar
Abstract. This paper studies how the unprecedented expansion of unemployment insurance during the pandemic affected wage inflation across the income distribution, decomposing its sources between within-firm wage growth and reallocation toward higher-paying firms. Using data from the Current Population Survey, we document that the recovery featured strong wage gains and increased job-to-job mobility at the bottom of the wage distribution, leading to a temporary compression of wages. To rationalize these patterns, we develop a general equilibrium wage-posting model with incomplete markets, risk-averse workers, and aggregate uncertainty. In the model, workers differ in wealth and face liquidity constraints that make job mobility risky, since firms gradually learn match quality and terminate low-quality matches among new hires. More generous UI benefits raise workers’ outside options and relax liquidity constraints, leading firms to post higher wages and workers to move more frequently toward high-wage firms. These mechanisms increase labor market tightness and compress the wage distribution, contributing to both the wage inflation and the reduction in wage inequality observed after the pandemic.
Abstract. I study how pay transparency and equal pay legislation affect within-firm wage inequality and workers’ bargaining power. Specifically, I examine the 2018 Massachusetts Equal Pay Act (MEPA), which prohibits employers from requesting salary histories, bans pay-secrecy policies, and mandates equal pay for comparable work. Using matched employer–employee data, I plan to implement a difference-in-differences design to estimate the causal impact of MEPA on within-firm wage dispersion among comparable roles. To interpret the empirical results, I develop a search-and-matching model in which workers and firms bargain under asymmetric information about outside offers. MEPA’s restrictions reduce informational asymmetries, shifting bargaining power toward workers and compressing the within-firm wage distribution. The model provides a framework to quantify the welfare and efficiency effects of transparency policies. This project aims to shed light on the role of information frictions in wage setting and to evaluate how institutional reforms that promote pay transparency can reduce inequality within firms.