Why do productive workers and firms locate together in dense cities? I develop a new theory of two-sided sorting in which both heterogeneous workers and firms sort across space. The location choices of workers and firms affect each other and endogenously generate spatial disparities in the presence of three essential forces: complementarity between worker and firm productivity, random matching within frictional local labor markets, and congestion costs. I demonstrate that the decentralized equilibrium exhibits excessive concentration of workers and firms, and dispersing them away from dense locations can mitigate congestion without reducing output. I then provide direct empirical evidence of the two-sided sorting mechanism using German administrative microdata. An exogenous increase in the quality of the workforce in a location results in more productive firms choosing that location. Finally, to quantify the implications of the model, I calibrate it to U.S. regional data and show that policies that relocate workers and firms toward less dense areas can increase welfare.

We study the importance of spatial firm sorting for wage inequality both between and within local labor markets. We develop a novel model in which heterogeneous firms first choose a location and then hire workers in a frictional local labor market. Firms' location choices are guided by a fundamental trade-off: Operating in productive locations increases output per worker, but sharing a labor market with other productive firms makes it hard to poach and retain workers, thereby limiting firm size. Positive firm sorting—with more productive firms settling in more productive locations—emerges as the unique equilibrium if firm and location productivity are sufficient complements or labor market frictions are sufficiently large. We show that positive firm sorting increases both the mean and the dispersion of wages in productive markets relative to less productive ones. The main mechanism is that firm sorting steepens the job ladder in productive places. We estimate our model using administrative data from Germany and identify firm sorting from a novel fact: Average local labor shares are lower in productive locations, which indicates a higher concentration of top firms with strong monopsony power. Quantitatively, positive firm sorting can account for at least 15% of the spatial variation in average wages and at least 40% of the spatial variation in within-location wage dispersion.

Why are economic activities concentrated in space? What are the policy implications of this concentration? And how do we expect it to change in the future? We revisit these classic questions in the context of non-tradable services, such as restaurants and retail, in Seoul. To understand the spatial concentration of services, we first causally identify positive spillovers across services stores. We microfound these spillovers by incorporating the trip-chaining mechanism—whereby consumers make multiple purchases during their services travel—into a quantitative spatial model that endogenizes the spatial distribution of services. When calibrated to an original survey on trip chaining, this mechanism explains about one-third of the observed concentration. However, unlike standard agglomeration mechanisms, it does not lead to inefficiency nor it exacerbates welfare inequality. Finally, we show that spatial linkages of services consumption play a crucial role in shaping the impact of the rise of work from home and of delivery services on the distribution of services.

In this paper, we develop a sufficient statistics approach to evaluate the impact of sectoral shocks on labor market dynamics and welfare. Within a broad class of dynamic discrete choice models that allows for arbitrary persistent heterogeneity across workers, we show that knowledge of steady-state worker flows across sectors over different time horizons is sufficient to construct counterfactual predictions on labor reallocation and welfare changes, up to a first-order approximation. We also establish analytically that assuming away persistent worker heterogeneity, a common practice in existing literature, necessarily leads to overestimation of steady-state worker flows, resulting in systematic biases in counterfactual predictions. As an illustration of our sufficient statistics approach, we revisit the consequences of the rise of import competition from China. Using US panel data to measure steady-state worker flows prior to the shock, we conclude that the labor reallocation away from manufacturing is significantly slower, and the negative welfare effects on manufacturing workers are much more severe than those predicted by earlier models that abstract from persistent worker heterogeneity.