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Metropolitan Labor Productivity and Urban Spatial Structure

A Comparison of U.S. Monocentric and Polycentric Metropolitan Areas

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Part of the book series: Advances in Spatial Science ((ADVSPATIAL))

Abstract

This paper questions the extent to which agglomeration economies can develop in a cluster of close-by cities, so-called polycentric metropolitan areas or polycentric urban regions (PURs). Theory suggests that agglomeration economies are nowadays increasingly associated with more dispersed spatial structures. Are polycentric metropolitan areas, despite their polycentric spatial layout, able to reap the advantages of urban size to a similar extent as monocentric metropolitan areas? By means of a novel method, the most monocentric metropolitan areas (a MSA or CSA dominated by a single city) and most polycentric metropolitan areas (MSAs or CSAs in which population is rather evenly distributed over their constituent cities) in the USA are identified. Polycentric metropolitan areas are furthermore divided into conurbations and polycentric metropolitan areas proper, which is based on the question of whether the cities in a polycentric metropolitan area are part of a contiguous urban area (conurbation) or not. Labor productivity serves as a proxy for agglomeration economies. Using 2006 data, strong evidence was found for metropolitan labor productivity, and hence agglomeration economies, being higher in polycentric metropolitan areas compared to monocentric ones. Referring to Alonso, this means that in polycentric metropolitan areas, cities are able to ‘borrow size’ from each other. The findings suggest that the location of a city nearby other relatively similar-sized cities results in a ‘borrowed size’ effect of 11 % in polycentric metropolitan areas. This borrowed size effects suggests that polycentric metropolitan areas on average outperform monocentric, single cities, controlling for the size of the urban population, urban density, human capital and the structure of the metropolitan economy. A similar result is found when explaining mean annual wages, with an elasticity of polycentricity of 5.7 %. Polycentric conurbations resemble monocentric metropolitan areas more than polycentric metro areas. Furthermore, it is demonstrated that while many sectors of economic activity have a stronger presence in monocentric metropolitan areas, productivity in many sectors tends to be higher in polycentric metropolitan areas. One explanation is that the spatial range of agglomeration advantages has been regionalized, while agglomeration diseconomies remain relatively more limited to the local level.

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Notes

  1. 1.

    Although there is an increased interest in mega-regions or ‘megapolitan’ regions on an even larger scale (see Carbonell and Yaro 2005; Lang and Dhavale 2005; Florida et al. 2008) and many ideas behind the PUR concept are likely to hold for such larger regions.

  2. 2.

    As ‘metropolitan area’ is the common term for a city-region or urban region in the US, we will refer to PURs in the US context as ‘polycentric metro area’, its antonym obviously being ‘monocentric metro area’.

  3. 3.

    Developed by Spiekermann and Wegener.

  4. 4.

    Only considering incorporated places of at least 5,000 inhabitants in 2006. In those cases where the second incorporated place did not meet this threshold, we used its actual size in order to be able to calculate a slope.

  5. 5.

    Metropolitan and micropolitan statistical areas (metro and micro areas; MSAs) are geographic entities defined by the U.S. Office of Management and Budget (OMB). A metro area contains a core urban area with a population of 50,000 or more, and a micro area contains an urban core with a population of at least 10,000 (but less than 50,000). Each metro or micro area consists of one or more counties and includes the counties containing the core urban area, as well as any adjacent counties that have a high degree of social and economic integration (as measured by commuting to work – 25 % of employed residents working in the core) with the urban core. MSAs that are adjacent may be joined in order to form a Combined Statistical Area if the employment interchange is at least 25. Adjacent MSAs that have an employment interchange measure of at least 15 and less than 25 will combine if local opinion favors combination.

  6. 6.

    Note that this measurement method is basically scale-free. In stead of cities, one may prefer to look at the rank-size distribution of employment concentrations when studying polycentricity at the city-scale. Or, when studying the megaregions in the U.S., one may wish to consider the size distribution of metro areas within these megaregions. At the European scale, one would have to consider European equivalents of such mega-regions to describe the level of polycentricity. Therefore, the appropriate unit of analysis changes with the spatial resolution of the issue at stake.

  7. 7.

    Excluding the agriculture, fishing, hunting and mining sectors, as well as the public administration sector.

  8. 8.

    Excluding self employment.

  9. 9.

    Ideally the number of jobs is measured at the workplace rather than the place of residence. However, such job counts, provided through the Current Employment Statistics program, are not satisfactorily available at the level of metropolitan areas. We therefore rely on the American Community Survey estimates of the number of jobs in the main sectors of the economy (applying the NAICS definitions), in which respondents are registered at their place of residence. This seems, however, justified by the fact that we analyse CSAs and, if not applicable, MSAs, which are both defined on the basis of commuting patterns amongst others, in such a way that they represent large travel-to-work areas. In other words, the number of people working outside of the MSA or CSA in which they live is likely to be very limited.

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Acknowledgement

The paper has benefited from comments received during the workshop on ‘Metropolitan Regions: Preconditions and Strategies for Growth and Development in the Global Economy’, held in April 2008 in Linköping, Sweden, as well as from valuable comments by Martijn Burger and Erik Louw. The usual disclaimer applies. Financial support from the Netherlands Organisation for Scientific Research (NWO) is gratefully acknowledged.

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  1. OTB Research Institute for the Built Environment, Delft University of Technology, 5030, Delft, GA 2600, The Netherlands

    Evert J. Meijers

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  1. Economics, Finance & Statistics, Jönköping Int. Business School, Jönköping University, Gjuterigatan 5, Jönköping, 551 11, Sweden

    Johan Klaesson

  2. Economics, Finance and Statistics, Jönköping Int. Business School, University Jonköping, Gjuterigatan 5, Jönköping, 551 11, Sweden

    Börje Johansson

  3. Economics, Finance and Statistics, Jönköping Int. Business School, Jönköping University, Gjuterigatan 5, Jönköping, 551 11, Sweden

    Charlie Karlsson

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Meijers, E.J. (2013). Metropolitan Labor Productivity and Urban Spatial Structure. In: Klaesson, J., Johansson, B., Karlsson, C. (eds) Metropolitan Regions. Advances in Spatial Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32141-2_7

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