The topography of metropolitan employment: Identifying centers of employment in a polycentric urban area

“…We diverge slightly from Redfearn (2007) and adopt a spatial Appendix A. We also replicate the analysis using census tracts; however, substantial overdispersion in the should reflect areas with significantly higher density than their surroundings.…”

mentioning

confidence: 99%

Los Angeles employment concentration in the 21st century

2016

View full text Add to dashboard Cite

This paper is an empirical analysis of employment centers in the Los Angeles region from 1997-2014. Most extant work on employment centers focuses on identification methodology or their dynamics during a period of industrial restructuring from 1980-2000. This timely study examines hypotheses derived from more recent perspectives on urban concentration and dispersion including New Urbanism, Smart Growth, sustainable cities, and the recent Global Financial Crisis. We use point-based, rather than census tractbased employment data to analyze concentration across five key industries: knowledge-intensive business services (KIBS), retail, creative, industrial, and high-tech, emphasizing changes in center composition and boundaries. While using point data necessitates slight changes to the nonparametric identification method typically used, results show far greater change across centers than previous longitudinal studies. Only 43% of the land area that is in an employment center is part of one in both 1997 and 2014. Using a persistence score, centers range from stable to highly fluctuating, but emerging, persisting, and dying centers are found in core and fringe areas alike. KIBS are most associated with stable centers, while high tech employment is attracted toward emerging areas and retail exists throughout. Emerging centers are more likely to have greater accessibility, while industrial employment becomes far more concentrated in centers by 2014.

show abstract

“…Several variations on this approach have been proposed (Craig and Ng, 2001;Redfearn, 2007 (Lee, 2007). Though this approach has been most frequently used on employment data, it has been applied to other data sources as well, including nighttime light emissions (Chen et al, 2017).…”

Section: Methods Of Identifying Employment Centersmentioning

confidence: 99%

The Spatial Structure of US Metropolitan Employment: New Insights from LODES Data

Manduca¹

2018

Preprint

View full text Add to dashboard Cite

Urban researchers have long debated the extent to which urban employment is monocentric, polycentric, or diffuse. In this paper I use high-resolution data based on unemployment insurance records to show that employment in US metropolitan areas is not centralized but is spatially concentrated. Unlike residents, who form a continuous surface covering most parts of each MSA, jobs have a bimodal spatial distribution, with most blocks containing no jobs whatsoever and a small number having extremely high employment densities. Across the 100 largest MSAs about 75% of jobs are located on the 10% of built land in Census blocks with at least twice as many jobs as people. Further, most of these jobs are in clustered business districts of more than 5 contiguous employment blocks. These relative proportions are extremely consistent across MSAs, even though cities vary greatly in the physical density at which they are constructed. Motivated by these empirical regularities, I introduce an algorithm to identify contiguous business districts and classify them into four major types. Based solely on the relative densities of employment and population, this algorithm is both simpler to implement and more flexible than current approaches, requiring no metro-specific tuning parameters and no assumptions about urban form. As one output, it provides an inductive, data-driven method of identifying city centers for the purposes of urban economic analysis.

show abstract

The topography of metropolitan employment: Identifying centers of employment in a polycentric urban area

Cited by 159 publications

References 21 publications

A non-parametric test for industrial specialization

A non-parametric test for industrial specialization

Los Angeles employment concentration in the 21st century

The Spatial Structure of US Metropolitan Employment: New Insights from LODES Data

Contact Info

Product

Resources

About