Essays on Labor Markets and Cities

This thesis focuses on the functioning of labor markets and on how search frictions affect the dynamics of labor productivity across space (first chapter) and over time (second chapter). The first chapter addresses a long-standing question concerning the sources of the positive wage differential between large and small US cities. I build a spatial equilibrium model that I use to measure the contribution of three channels. In the model, larger cities are characterized by a higher frequency of interactions in the labor market–hence better matches between workers and firms (matching)–a better composition of peers workers learn from (knowledge diffusion), and positive sorting of high-skilled workers through migration across cities (sorting). I find that the aggregate implications of policies that change the size and composition of cities are determined by how such policies influence matching, knowledge diffusion, and sorting. Concretely, I show that an expansion of housing supply in large, productive, cities reduces the extent of sorting and knowledge diffusion in those cities. As a consequence, the aggregate income gain from implementing such policy is considerably smaller than in a hypothetical scenario in which the productivity of cities was invariant to the policy. The second chapter extends the traditional search and matching model of the labor market to account for long-run growth in the efficiency of the search technology. We provide necessary and sufficient conditions under which such long-run growth does not trigger a secular decline in unemployment (consistently with US data), but it contributes to labor productivity growth. Intuitively, a higher meeting probability in the labor market allows firm-worker pairs to be more selective with respect to the quality of the matches they create. Simple calculations show that this channel may be responsible for approximately one fourth of US labor productivity growth over the last 30 years