Shared Skills: Occupation Clusters for Poverty Alleviation and Economic Development in the US

Abstract

Economic development scholars and practitioners increasingly recognise the importance of both industry and occupational composition as sources of regional strength and specialisation. At the same time, occupational cluster analysis has paid insufficient attention to a main potential constituency of economic development: people in or near poverty. This article addresses this gap by developing 25 occupation clusters using a wide range of attributes, including skills and work styles, available from US Occupational Information Network (O*NET) data. The resulting clusters include many lower-wage occupations and illustrate possible career paths within clusters and across industries, based on similar interests and abilities, among other factors. These occupation clusters can be used to define the labour pools in US regions. Two of these clusters are used to demonstrate the concept that economic development centred on existing labour assets in a particular city or region may lead to stronger growth as well as reduced poverty.

Innovation Districts and Community Building: An Effective Strategy for Community Economic Development?

“…At his final inaugural address in 2010, long-time Boston Mayor Thomas Menino unveiled his intentions to transform the South Boston Seaport into an innovation district modeled after Barcelona@22 (The Honorable Thomas M. Menino Inaugural Address, 2010). The Big Dig, a decades-long multibillion-dollar infrastructure project, primed the area for investment by connecting it to Logan Airport and the city center (Daniel, 2006). Early plans envisioning a new “Downtown South” never fully materialized, though the peninsula was home to existing communities such as Fort Point and South Boston.…”

A Measure of Interdependence: Skill in the Supply Chain

“…The U.S. Department of Labor's Bureau of Labor Statistics Occupational Employment Statistics (BLS OES) occupation data are often used in studies of occupational trends and occupational clusters (Chrisinger et al, 2012;Feser, 2003;Koo, 2005;Markusen & Schrock, 2001;Renski et al, 2007;U.S. BLS, 2016a).…”

“…For municipalities that are home to large populations of lower-wage workers, occupational clustering techniques can identify accessible career pathways across existing industry. Recognizing that the "knowledge-based clusters" proposed by Feser (2003) and Koo (2005) were not accessible to people in or near poverty, Chrisinger, Fowler, and Kleit (2012) identified clusters accessible to low-wage workers and argued that economic development centered on these clusters could boost growth and reduce poverty. They highlighted the possibility of linking not only displaced workers to jobs requiring their skill profile but also workers stuck in deadend jobs to better jobs in related fields, suggesting that workers can incrementally increase skills and compensation across occupations and industries when work at a single firm or in a single industry does not necessarily ensure advancement.…”

“…Consequently, smaller firms likely have difficulty taking advantage of local labor pools. Chrisinger et al (2012) suggested that local labor pools of low-wage workers should be the subjects of economic development efforts to reduce poverty. They leave us asking how we can increase the number of accessible occupations.…”

State Tax Policy, Municipal Choice, and Local Economic Development Outcomes: A Structural Equation Modeling Approach to Performance Assessment

“…These include such factors as jobs, income, economic diversity, quality of life, income inequality, and poverty (Besser, Recker, and Parker 2009, 309). Poverty or socioeconomic status is commonly considered both a control variable and a measure of economic development outcomes (Blank 2005; Chrisinger, Fowler, and Kleit 2012; Hall and Howell‐Moroney 2012; Partridge and Rickman 2005; Shin and Hall 2018). Others consider changes in property values (Byrne 2006), including home values (Tao and Feiock 1999).…”