UC Berkeley

A prominent feature of the economic landscape in the most developed countries is the tendency for firms to locate near other firms producing similar products or services. In the United States, for example, biopharmaceutical firms are clustered in New York and Chicago and a sizeable share of the elevator and escalator industry is concentrated in the area around Bloomington, Indiana. In addition, the growth and diffusion of multinational corporations has led to the recent appearance of important industrial clusters in several emerging economies. Firms that originally agglomerated in Silicon Valley and Detroit now have subsidiaries clustered in Bangalore and Slovakia.

Researchers have long speculated that firms in industrial concentrations may benefit from agglomeration economies, and a growing body of work has been devoted to studying the importance of these economies. Despite the difficulties involved in estimating agglomeration effects, a consensus has emerged from the literature that significant productivity advantages of agglomeration exist for many industries (Rosenthal and Strange, 2003; Henderson, 2003; Ellison, Glaeser and Kerr, 2010; Greenstone, Hornbeck and Moretti, 2010; Combes et al., 2012). Localized knowledge spillovers are a common explanation for the productivity advantages of agglomeration.

Nevertheless, as pointed out by Combes and Duranton (2102) if information can easily flow out of firms, the question of why the effects of spillovers are localized must be clarified.

This dissertation directly examines the role of labor mobility as a mechanism for the transfer of efficiency-enhancing knowledge and evaluates the extent to which labor mobility can explain the productivity advantages of firms located near other highly productive firms. The underlying idea is that knowledge is embedded in workers and diffuses when workers move between firms. The strong localized aspect of knowledge spillovers discussed in the agglomeration literature may thus arise from the propensity of workers to change jobs within the same local labor market.

In order to empirically assess the importance of labor-market based knowledge spillovers, I use matched employer-employee data from the centre and north-east of Italy (mainly Veneto, but also Emilia Romagna and Tuscany). While the issues analyzed in this study are of general interest, the case of this region is important because it is an economic area where networks of specialized small and medium-sized firms, frequently organized in districts, have been effective in promoting and adapting to technological change during the last three decades. This so called "Third Italy" region has received a good deal of attention by researchers, in the United States as well as in Europe.

In chapter 1, titled "Labor Mobility as a Mechanism for Knowledge Transfer", I present direct evidence on the role of firm-to-firm labor mobility in enhancing the productivity of firms located near highly productive firms. More specifically, I identify a set of high-wage firms (HWF) and show they are more productive than other firms. I then show that hiring a worker with HWF experience increases the productivity of other (non-HWF) firms.

In chapter 2, titled "Worker flows and Agglomeration Advantages", I relate the findings In Chapter 1 to the existing evidence on the productivity advantages of agglomeration. Simulation results indicate that worker flows explain 10-15 percent of the productivity gains experienced by other firms when HWFs in the same industry are added to a local labor market.

In chapter 3, titled "Mobility of Inventors and Innovation", my co-author Sabrina Di Addario and I investigate the relationship between worker flows and innovative activity. We use a unique dataset that matches administrative employer-employee records to patent data and focus on labor market mobility of inventors. While inventors are not the only workers that may transfer relevant information from one firm to another, they undoubtedly have a large potential to do so. Our preliminary results show that the number of workers who have applied for a patent while working at a previous firm is positively and statistically significantly related to patenting activity of the current firm's other employees.