We study the coagglomeration of domestic plants and foreign multinationals and the impact of this on domestic plant growth using data for Irish manufacturing. To this end we make use of the index developed by Ellison and Glaeser (1997) and find coagglomeration to be important for a number of sectors. Foreign presence as well as foreign employment density are found to be important determinants of employment growth over the period, especially for those sectors with a high degree of coagglomeration.

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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

This paper presents on overview of the economics that lies behind social interaction models and briefly discusses the empirical approaches to social interactions. We present a simple model with local interactions, similar to Glaeser, Sacerdote and Scheinkman (1996) but using a continuous action space and starting with optimizing behavior. We then extend the model to include both global and local interactions. We suggest and use a methodology for using variation of intra-city aggregates to identify the relative sizes of local and global interactions. We also present a model with endogenous location choice and use the predictions of that model to identify the sources of cross-city variance that are due to sorting and interaction. Finally, we present a brief discussion of using time-series to estimate the social interactions in broad aggregates.

We use a novel dataset and research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than individuals in nearby but not identical blocks. We find significant evidence of social interactions; the baseline probability of working together is 0.93 % at the block level compared to 0.51 % at the block group level (a collection of ten contiguous blocks). We also provide evidence as to which types of matches between individuals result in greater levels of referrals. These findings are robust to the introduction of detailed controls for socio-demographic characteristics and block group fixed effects, as well as across various specifications intended to address sorting and housing market rather than labor market referrals. Further, our estimated effects have a significant impact on a wide range of labor market outcomes more generally.

A number of potential advantages of industry agglomeration—or spatial clustering—have since long been identified in the research literature, notably related to shared costs for infrastructure, the build up of a skilled labour force, transaction efficiency, and knowledge spill-overs leading to firm learning and innovation. We identify two shortcomings of existing research on the clustering phenomenon. First, the abundance of theoretical concepts stands in sharp contrast with the general lack of work aiming to validate these mechanisms empirically and the contradictory evidence found in recent empirical work in the field. Secondly, there is a lack of a unified theoretical framework for analyzing spatial clustering. In an attempt to remedy the second shortcoming, this paper investigates the nature of the cluster from a knowledge creation or learning perspective. We argue for the need to establish a specific theory of the cluster where learning occupies center stage. The basic requirements for such a theory of the cluster are discussed. Two main components of such a theory are identified: it must explain the existence of the cluster on the one hand and its internal organization on the other.

This paper develops micro-foundations for the role that diversified cities play in fostering innovation. A simple model of process innovation is proposed, where firms learn about their ideal production process by making prototypes. We build around this a dynamic general equilibrium model, and derive conditions under which diversified and specialised cities coexist in steady-state. New products are developed in diversified cities, trying processes borrowed from different activities. On finding their ideal process, firms switch to mass-production and relocate to specialised cities where production costs are lower. We find strong evidence of this pattern in establishment relocations across French employment areas 1993–1996.

This chapter examines empirical strategies that have been or could be used to evaluate the importance of agglomeration and trade models. This theoretical approach, widely known as “New Economic Geography” (NEG), emphasizes the interaction between transport costs and firm-level scale economies as a source of agglomeration. NEG focuses on forward and backward trade linkages as causes of observed spatial concentration of economic activity. We survey the existing literature, organizing the papers we discuss under the rubric of five interesting and testable hypotheses that emerge from NEG theory. We conclude the chapter with an overall assessment of the empirical support for NEG and suggest some directions for future research.

A paradox has been the emergence of the importance of local proximity and geographic clusters precisely at a time when globalization seems to dominate economic activity. The purpose of this paper is to resolve this paradox by explaining why and how geography matters for innovative activity and ultimately for the interna-tional comparative advantage. Globalization and the telecommunications revolution have triggered a shift in the comparative advantage of the leading developed countries towards an increased importance of innovative activity. This shift in comparative advantage has increased the value of knowledge-based economic activity. Since knowledge is generated and transmitted more efficiently via local proximity, economic activity based on new knowledge has a high propensity to cluster within a geographic region. This has triggered a fundamental shift in public policy towards business, away from policies constraining the freedom of firms to contract and towards a new set of enabling policies, implemented at the regional and local levels. I.

assistance. The authors also gratefully acknowledge support provided by the Council on Competitiveness. Stern