acknowledged. Research results and conclusions expressed are those of the authors and do not necessarily reflect the We quantify agglomeration spillovers by estimating the impact of the opening of a large new manufacturing plant on the total factor productivity (TFP) of incumbent plants in the same county. Articles in the corporate real estate journal Site Selection reveal the county where the “Million Dollar Plant ” ultimately chose to locate (the “winning county”), as well as the one or two runner-up counties (the “losing counties”). The incumbent plants in the losing counties are used as a counterfactual for the TFP of incumbent plants in winning counties in the absence of the plant opening. Incumbent plants in winning and losing counties have economically and statistically similar trends in TFP in the 7 years before the opening, which supports the validity of the identifying assumption. After the new plant opening, incumbent plants in winning counties experience a sharp relative increase in TFP. Five years after the opening, TFP of incumbent plants in winning counties is 12 % higher than TFP of incumbent plants in losing counties. Consistent with some theories of agglomeration, this effect is larger for incumbent plants that share similar labor and technology pools with the new plant. We also find evidence of a relative increase in skill-adjusted labor costs in winning counties, indicating that the

Abstract: Firms and workers are much more productive in large and dense urban environments. There is substantial evidence of such agglomeration economies based on three aproaches. First, on a clustering of production beyond what can be explained by chance or comparative advantage. Second, on spatial patterns in wages and rents. Third, on systematic variations in productivity with the urban environment. However, more needs to be learned about the causes of agglomeration economies. We have good models of agglomeration through sharing and matching, but not a deep enough understanding of learning in cities. Despite recent progress, more work is needed to distinguish empirically between alternative causes. Key words: agglomeration economies. jel classification: r30 This paper has been written for the Journal of Regional Science’s 50 th

We estimate the factors determining specialization of crop choice at the level of individual fields, distinguishing between the role of natural advantage (soil characteristics) and economies of density (scale economies achieved when farmers plant neighboring fields with the same crop). Using rich geographic data from North Dakota, including new data on crop choice collected by satellite, we estimate the analog of a social interactions econometric model for the planting decisions on neighboring fields. We find that planting decisions on a field are heavily dependent on the soil characteristics of the neighboring fields. Through this relationship, we back out the structural parameters of economies of density. Setting an Ellison-Glaeser dartboard level of specialization as a benchmark, we find that of the actual level of specialization achieved beyond this benchmark, approximately two-thirds can be attributed to natural advantage and one-third to density economies.

Why do levels of entrepreneurship differ across America’s cities? This paper presents basic facts on two measures of entrepreneurship: the self-employment rate and the number of small firms. Both of these measures are correlated with urban success, suggesting that more entrepreneurial cities are more successful. There is considerable variation in the self-employment rate across metropolitan areas, but about one-half of this heterogeneity can be explained by demographic and industrial variation. Self-employment is particularly associated with abundant, older citizens and with the presence of input suppliers. Conversely, small firm size and employment growth due to unaffiliated new establishments is associated most strongly with the presence of input suppliers and an appropriate labor force. I also find support for the Chinitz (1961) hypothesis that entrepreneurship is linked to a large number of small firms in supplying industries. Finally, there is a strong connection between area-level education and entrepreneurship. 1 Kristina Tobio provided superb research assistance and oversaw a team consisting of Yün-ke Chin-Lee, Elizabeth

This paper was prepared for the “Handbook of Economic Geography and Industry Studies ” to be published by Edward Elgar Publishing. The authors especially thank Jake Carr and Robert O’Loughlin for excellent research assistance. This paper has benefited from comments from Robert Hunt, Leonard Nakamura, and Tony Smith. We alone are responsible for any remaining errors. The views expressed here are those of the authors and do not necessarily represent the views of the Federal Reserve Bank of Philadelphia or the Federal Reserve System. This paper is available free of charge at www.philadelphiafed.org/research-and-data/publications/workingpapers/.WORKING PAPER NO. 09-16

Bryson, Keith Maskus, and Debbie Smeaton for comments and data assistance. The research in this paper was conducted while the authors were Special Sworn Status researchers of the U.S. Census Bureau at the Boston Census Research Data Center (BRDC). Support for this research from NSF grant (ITR-0427889) is gratefully acknowledged. Research results and conclusions expressed are our own and do not necessarily reflect the views of the Census Bureau or NSF. This paper has been 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 Bureau’s 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 Marshall’s 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

This paper presents a survey of recent research on the economics of infrastructure in developing countries. Energy, transport, telecommunications, water and sanitation are considered. The survey covers two main set of issues: the linkages between infrastructure and economic growth (at the economy-wide, regional and sectoral level) and the composition, sequencing and efficiency of alternative infrastructure investments, including the arbitrage between new investments and maintenance expenditures; OPEX and CAPEX, and public versus private investment. Following the introduction, section 2 discusses the theoretical foundations (growth theory and new economic geography). Section 3 assesses the analysis of 140 specifications from 64 recent empirical papers— examining type of data used, level of aggregation, econometric techniques and nature of the sample—and discusses both the macro-econometric and microeconometric contributions of these papers. Finally section 4 discusses directions for future research and suggests priorities in data development.

to Dennis Epple, Lowell Taylor and Bill Vogt for very helpful comments. The customary disclaimers apply. The views expressed herein are those of the authors and do not necessarily reflect the views

This paper presents a dynamic investment game in which firms that are initially identical develop assets which are specialized to different market segments. The model assumes there are increasing returns to investment in a segment, for example, due to word-of-mouth or learning curve effects. In equilibrium, firms that are only slightly different focus all of their investment in different segments, causing small random differences to expand into large permanent differences. Even though firms do not cooperate and do not make threats to punish each other, in the long run they divide the market, reaching the same outcome that they would if they cooperated to maximize joint profits. I am grateful to my advisor, Birger Wernerfelt, for his support and guidance. Helpful comments

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 …nd 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 di ¢ cult to identify ex ante, which is why democratizing entry is an important trait of well-functioning capital markets.