This thesis is comprised of three chapters. The first investigates the implications of industrial clustering for labor mobility and earnings dynamics. Motivated by a theoretical model in which geographically clustered firms compete for workers, I exploit establishment-level variation in agglomeration to explore the impact of clustering in the software publishing industry on labor market outcomes. The results show that clustering makes it easier for workers to job hop among establishments within the sector. Further, workers in clusters have relatively steep earnings-tenure profiles, accepting lower wages early in their careers in exchange for stronger earnings growth and higher wages later. These findings underscore the importance of geography in understanding labor market dynamics within industries.

While the first chapter reveals striking relationships between the human resource practices and location decisions of high-technology establishments, the second chapter (joint with F. Andersson, J. Haltiwanger, J. Lane, and K. Shaw) draws key connections between the hiring and compensation policies of innovative firms and the nature of their product markets. We show that software firms that operate in product markets with highly skewed returns to innovation pay a premium to attract talented workers. Yet these same firms also reward loyalty; that is, highly skilled workers faithful to their employers enjoy higher earnings in firms with a greater variance in potential payoffs from innovation. These results not only contribute to our knowledge of firm human resource practices and product market strategies, but also shed light on patterns of income inequality within and between industries.

Building on this final idea, the last chapter (joint with F. Andersson, E. Davis, J. Lane, B. McCall, and L. Sandusky) examines the contribution of worker and firm reallocation to within-industry changes in earnings inequality. We find that the entry and exit of firms and the sorting of workers and firms based on worker skills are key determinants of changes in industry earnings distributions over time. However, the importance of these and other factors in driving observed dynamics in earnings inequality varies across sectors, with aggregate shifts often disguising fundamental differences in the underlying forces effecting change.