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URBAN SPATIAL STRUCTURE AND ECONOMIC GROWTH IN US METROPOLITAN AREAS Western Regional Science Association 46th Annual Meeting Newport Beach, California February, 2007 Bumsoo Lee* and Peter Gordon University of Southern California Los Angeles, CA 90089-0626 January, 2007 JEL classification: R14 Key Words: Urban Spatial Structure, Jobs Dispersion, Metropolitan Growth * Corresponding author.ABSTRACT This paper presents an empirical study of the links between metropolitan spatial structure and economic growth. Consistent with an urban evolution hypothesis, the growth effects of employment dispersion were found to be dependent on metropolitan size. A metropolitan area with a more clustered spatial form grows faster, perhaps enjoying agglomeration economies when it is small; whereas more dispersion leads to higher growth rates as metro areas grow large. Just as a city needs to successfully take on higher-order functions and economic activities to move upward within the national urban system, it also needs to restructure its spatial form in a way to mitigate congestion or other diseconomies of size for continued growth. Therefore, attempts to find one specific efficient urban form – at least with respect to growth – may not be promising, just as the efforts to find an optimal city size have not been fruitful.11. INTRODUCTION Does urban spatial structure influence economic performance or growth in metropolitan areas? Is one particular type of urban form more efficient than another? Or is the efficient spatial structure contingent on the size and other attributes pertaining to each metropolitan area? We address these questions by investigating the links between urban spatial structure and economic growth in a cross section of 79 US metropolitan areas. In particular, we probe into the question how these links relate to metropolitan size. Considerable evidence has accumulated on the existence and extent of agglomeration economies (for surveys of the literature, see Moomaw 1983; Gerking 1994). In general, firms in large cities tend to have higher productivity because they can either lower production costs or facilitate competitive innovation due to agglomeration economies arising from a variety of sources.1 Not only firms but also people tend to have more chances to learn and acquire skills in urban agglomerations that ensure them higher returns (Glaeser 1999). Moreover, consumers in larger cities enjoy a variety of specialized goods and services, and cultural and entertainment opportunities (Clark, Kahn, and Ofek 1988). High-end restaurants and Broadway shows in Manhattan and professional sports teams in big cities are examples. However, urban growth is not without costs. Firms and households in large cities also suffer from negative externalities such as congestion, pollution, and higher crime rates. The trade-off between these agglomeration economies and diseconomies has provided a rationale for the attempts to define an optimal city size (Carlino 1987). Optimal city size, in 1 Various types and sources of agglomeration economies are discussed in the literature. These include internal scale economies, localization economies – arising from labor market pooling, technological spillovers, intra-industry specialization and scale economies of industry specific infrastructure – and urbanization economies – arising from specialized business services, public infrastructure and ‘law of large numbers’ (Mills 1994; Richardson 1995; Eberts and McMillen 1999). More recent literature emphasizes the role of innovative process localized within urban clusters (Malmberg 1996; Porter 2000). Whereas manufacturing sectors tend to benefit more from specialization and localization economies (Henderson 1986; Moomaw 1988; Henderson, Kuncoro, and Turner 1995), urban diversity and localized competition2general, derived as the maximal point of agglomeration economies net of associated diseconomies are supposed to be an inverted U-shaped function of city size (Begovic 1991). Some early studies attempted to find the minimal point of U-shaped cost curves of urban public services (Clark 1945; Hirsch 1959). However, the notion of optimal city size was criticized on the grounds that there coexist cities of various sizes in a national urban hierarchy, through which specialized goods and services are delivered, and innovation and other economic functions are channeled across cities (Richardson 1972). And relative size distributions of cities have been remarkably stable over time in most countries (Eaton and Eckstein 1997; Black and Henderson 1999, 2003; Nitsch 2003). Many have been shown to obey Zipf’s law or the rank-size rule (Gabaix 1999). Although economic reasons for the empirical regularity are still murky, it implies parallel urban growth patterns in relation to city size rather than convergence to a particular optimal city size (Barnard and Krautmann 1988; Eaton and Eckstein 1997; Glaeser, Scheinkman, and Shleifer 1995)2. Within the hierarchical urban system, cities at different ranks (different size) take on different economic functions with variant ‘efficient sizes’ (Richardson 1972; Capello and Camagni 2000). Hence, the prospective growth of a city depends on “its ability to move to ever higher urban ranks, developing or attracting new and superior functions (Camagni, Diappi, and Leonardi 1986)”. Prud’homme and Lee (1999) made a similar point by suggesting that good city management – transportation and land use policy – can shift marginal benefits of city size upward and costs downward, increasing the efficient city size. Empirically, upward mobility within the US urban hierarchy for the last century was found to be promoted by favorable geographical are found to be contributing to more innovation and growth in more knowledge intensive sectors (Glaeser et al. 1992; Harrison, Kelley, and Gant 1996; Feldman and Audretsch 1999; Combes 2000). 2 Wheeler (2003) found an ‘inverted U-shaped’ growth pattern in a cross-section of US counties, but not in metropolitan level data in the 1980s. We interpret the county level results as the growth with fixed geographical boundary.3amenities – climate and coastal location – and higher market potential (Black and Henderson 1999, 2003). The links between urban form and growth can be understood in this context of urban evolution. To the extent that a city can adjust its spatial


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