William R. Kerr

What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns

Many industries are geographically concentrated. Many mechanisms that could account for such agglomeration have been proposed. We note that these theories make different predictions about which pairs of industries should be coagglomerated. We discuss the measurement of coagglomeration and use data from the Census Bureaus Longitudinal Research Database from 1972 to 1997 to compute pairwise coagglomeration measurements for U.S. manufacturing industries. Industry attributes are used to construct measures of the relevance of each of Marshalls three theories of industry agglomeration to each industry pair: (1) agglomeration saves transport costs by proximity to input suppliers or final consumers, (2) agglomeration allows for labor market pooling, and (3) agglomeration facilitates intellectual spillovers. We assess the importance of the theories via regressions of coagglomeration indices on these measures. Data on characteristics of corresponding industries in the United Kingdom are used as instruments. We find evidence to support each mechanism. Our results suggest that input-output dependencies are the most important factor, followed by labor pooling.

Ethnic Scientific Communities and International Technology Diffusion

This study explores the role of U.S. ethnic scientific and entrepreneurial communities for international technology transfer to their home countries. U.S. ethnic researchers are quantified through an ethnic-name database and individual patent records. International patent citations confirm knowledge diffuses through ethnic networks, and manufacturing output in foreign countries increases with an elasticity of 0.10.3 to stronger scientific integration with the U.S. frontier. Specifications exploiting exogenous changes in U.S. immigration quotas address reverse-causality concerns. Exercises further differentiate responses by development stages in home countries. Ethnic technology transfers are particularly strong in high-tech industries and among Chinese economies.

Does Employment Protection Reduce Productivity? Evidence From US States*

Theory predicts that mandated employment protection may reduce productivity by distorting production choices. We use the adoption of wrongful-discharge protection by state courts in the US from 1970 to 1999 to evaluate the empirical link between dismissal costs and productivity. Drawing on establishment-level data from the Census Bureau, our estimates suggest that wrongful-discharge protection reduces employment flows and firm entry rates. Moreover, plants engage in capital deepening and experience a decline in total factor productivity, indicative of altered production techniques. Evidence of strong contemporaneous growth in employment, however, leads us to view our findings as suggestive but tentative.

Democratizing Entry: Banking Deregulations, Financing Constraints, and Entrepreneurship

We examine entrepreneurship and creative destruction following US banking deregulations using Census Bureau data. US banking reforms brought about exceptional growth in both entrepreneurship and business closures. The vast majority of closures, however, were the new ventures themselves. Although we do find evidence for the standard story of creative destruction, the most pronounced impact was a massive increase in churning among new entrants. We argue that creative destruction requires many businesses failures along with the few great successes. The successes are very difficult to identify ex ante, which is why democratizing entry is an important trait of well-functioning capital markets.

The Supply Side of Innovation: H-1B Visa Reforms and US Ethnic Invention

This study evaluates the impact of high-skilled immigrants on US technology formation. We use reduced-form specifications that exploit large changes in the H-1B visa program. Higher H-1B admissions increase immigrant science and engineering (SE) employment and patenting by inventors with Indian and Chinese names in cities and firms dependent upon the program relative to their peers. Most specifications find limited effects for native SE employment or patenting. We are able to rule out displacement effects, and small crowding-in effects may exist. Total SE employment and invention increases with higher admissions primarily through direct contributions of immigrants.

Clusters of entrepreneurship

Employment growth is strongly predicted by smaller average establishment size, both across cities and across industries within cities, but there is little consensus on why this relationship exists. Traditional economic explanations emphasize factors that reduce entry costs or raise entrepreneurial returns, thereby increasing net returns and attracting entrepreneurs. A second class of theories hypothesizes that some places are endowed with a greater supply of entrepreneurship. Evidence on sales per worker does not support the higher returns for entrepreneurship rationale. Our evidence suggests that entrepreneurship is higher when fixed costs are lower and when there are more entrepreneurial people.

Growth Through Heterogeneous Innovations

We study how exploration versus exploitation innovations impact economic growth through a tractable endogenous growth framework that contains multiple innovation sizes, multi-product firms, and entry/exit. Firms invest in exploration R&D to acquire new product lines and exploitation R&D to improve their existing product lines. We model and show empirically that exploration R&D does not scale as strongly with firm size as exploitation R&D. The resulting framework conforms to many regularities regarding innovation and growth differences across the firm size distribution. We also incorporate patent citations into our theoretical framework. The framework generates a simple test using patent citations that indicates that entrants and small firms have relatively higher growth spillover effects.

Innovation, Reallocation and Growth

We build a model of firm-level innovation, productivity growth and reallocation featuring endogenous entry and exit. A new and central economic force is the selection between high- and low-type firms, which differ in terms of their innovative capacity. We estimate the parameters of the model using US Census micro data on firm-level output, R&D and patenting. The model provides a good fit to the dynamics of firm entry and exit, output and R&D. Taxing the continued operation of incumbents can lead to sizable gains (of the order of 1.4% improvement in welfare) by encouraging exit of less productive firms and freeing up skilled labor to be used for R&D by high-type incumbents. Subsidies to the R&D of incumbents do not achieve this objective because they encourage the survival and expansion of low-type firms.

Breakthrough inventions and migrating clusters of innovation

We investigate the speed at which clusters of invention for a technology migrate spatially following breakthrough inventions. We identify breakthrough inventions as the top one percent of US inventions for a technology during 1975-1984 in terms of subsequent citations. Patenting growth is significantly higher in cities and technologies where breakthrough inventions occur after 1984 relative to peer locations that do not experience breakthrough inventions. This growth differential in turn depends on the mobility of the technologys labor force, which we model through the extent that technologies depend upon immigrant scientists and engineers. Spatial adjustments are faster for technologies that depend heavily on immigrant inventors. The results qualitatively confirm the mechanism of industry migration proposed in models like Duranton (2007).

Clusters of Entrepreneurship and Innovation

This paper reviews recent academic work on the spatial concentration of entrepreneurship and innovation in the United States. We discuss rationales for the agglomeration of these activities and the economic consequences of clusters. We identify and discuss policies that are being pursued in the United States to encourage local entrepreneurship and innovation. While arguments exist for and against policy support of entrepreneurial clusters, our understanding of what works and how it works is quite limited. The best path forward involves extensive experimentation and careful evaluation.