The Structure of Sprawl: Identifying and Characterizing Employment Centers in Polycentric Metropolitan Areas

Article excerpt

WILLIAM T. BOGART [*]

ABSTRACT. This paper applies a consistent framework to four comparably sized metropolitan areas to identify and characterize their employment centers. Employment centers are identified as places that exceed a threshold employment density and a threshold employment level. They are also characterized as specializing on the basis of location quotient analysis. We find clear evidence of specialization in every employment center in the four metropolitan areas studied. Our interpretation is that what we are observing is a systematic change in metropolitan structure rather than a random sprawling of firms. We also find some evidence that the size distribution of employment centers follows the rank-size rule. This suggests that there is structure not only in the distribution of economic activity among the employment centers but also in their size distribution. Because less than 50 percent of metropolitan employment is within employment centers, future research should focus on understanding the more diffuse employment patterns. The rank-size rule gives some guidance as to the expected size distribution of employment throughout the metropolitan area.

I

Introduction

The sweeping changes in metropolitan structure in the United States have led many to decry urban sprawl as a blight on the landscape. However, it is possible that much of this metropolitan decentralization has not been sprawl in the sense of random scattering of people and firms but rather a change in structure to reflect changing technology and preferences. A growing literature in urban economics looks for common features of decentralized metropolitan areas.

This paper applies a consistent analytical framework to four comparably-sized metropolitan areas (Cleveland, Indianapolis, Portland, and St. Louis) to identify and characterize their employment centers. Employment centers are identified as places that exceed a threshold employment density and a threshold employment level. They are then characterized as specializing on the basis of location quotient analysis. If decentralization is occurring randomly, then we should find that some or all of the employment centers are not identified as specialized. We find, to the contrary, clear evidence of specialization in every employment center in these four metropolitan areas.

There is also some evidence that the size distribution of employment centers follows the rank-size rule. Theoretical models of urban growth are now expected to generate the rank-size rule for city size distributions. Our finding that the rank-size rule holds for intrametropolitan size distributions suggests that it is possible that similar processes govern the growth and development of the parts of a metropolitan area as govern the growth and development of the metropolitan area as a whole.

II

Identifying Employment Centers

An employment center is an area with both a high density and high quantity of employment. We use the transportation analysis zone (TAZ) as the geographical unit of analysis. A TAZ is composed of one or more census blocks, with the borders being supplied to the U.S. Census Bureau by the metropolitan planning organization in each metropolitan area. Our data are thus a snapshot of metropolitan structure in 1990. An interesting task for future research will be to link these snapshots (even at ten-year intervals) to better understand the dynamic processes driving metropolitan structure.

The methodology developed by Giuliano and Small (1991) in their study of Los Angeles requires identifying TAZs with dense employment, combining adjacent employment-dense TAZs into groups, and measuring total employment in the groups. An employment center is defined as a cluster of contiguous TAZs, all with gross employment density exceeding some minimum D, and with total employment exceeding some minimum E. McMillen and McDonald (1998) and Bogart and Ferry (1999) use this methodology to study Chicago and Cleveland respectively. …