UCLA

This dissertation is devoted to studying how workers initially match with firms, and are subsequently retained or reallocated over time. The first two chapters---one theoretical, the other empirical---specifically ask how asymmetric employer information distorts career placement and efficiency in a dynamic setting. The final chapter studies optimal dynamic compensation policy from the standpoint of a single employer attempting to maximize retention at minimum cost.

In Chapter 1, I develop a new framework to investigate the efficiency costs of asymmetric information in the labor market. I consider a setting where, similar to Greenwald (1986), employers have an inside advantage in learning their employees' abilities. I then add complementarity between firms' heterogeneous technologies and the abilities of their workers in order to study how asymmetric information can disrupt the efficient assignment of workers to firms. Workers' abilities are initially hidden and become privately observed by their employers. Incumbent firms retain high-ability workers. Low-ability workers separate to uninformed but comparatively advantaged outsiders where the returns to ability are low. Relative to a static optimum, new hires over-place into inefficiently high-type firms, and then become under-placed as they accumulate tenure. These placement distortions present an added source of inefficiency relative to a symmetric learning environment. I derive a variety of testable implications of the model, and prove a non-parametric method for identifying the surplus function.

In Chapter 2, I present evidence on how adverse selection and production complementarities interact to produce distinct patterns in reallocation. I build a new data-set on the US market for lawyers by linking together the Martindale-Hubbell professional directories from 1930-1963. I show evidence that lawyers who separate from surviving firms are adversely selected, and move to firms where their peers have lower average ability. Meanwhile, lawyers who separate after their firm exits move to firms with higher-ability peers, but are not positively selected compared to similar lawyers who are retained. These results provide evidence to support the asymmetric learning model of Chapter 1.

In Chapter 3, which is co-authored with Moshe Buchinsky and John de Figueiredo, we examine the cost-effectiveness of compensation policy in the federal government. We estimate a dynamic retention model using the federal government's personnel data, exploiting exogenous pay variation caused by the 1990s civil service pay reform known as the Federal Employees Pay Comparability Act (FEPCA). We find that the elasticity of retention to pay is typically around 25% for the workers in our sample. The model can be combined with assumptions about government hiring in order to make long-run out-of-sample forecasts of payroll costs, turnover, and workforce composition under alternative compensation policies.