Linking Industry and Occupation Clusters in Regional Economic Development

Nolan, Christine; Morrison, Ed; Kumar, Indraneel; Galloway, Hamilton; Cordes, Sam

doi:10.1177/0891242410386781

Cited by 37 publications

(39 citation statements)

References 7 publications

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“…(EMSI) with information on county employment and earnings disaggregated at 4--digit NAICS level. EMSI data have been successfully used in various studies in recent years (Betz et al, 2015;Dorfman et al, 2011;Fallah et al, 2011;Fallah et al, 2014;Nolan et al, 2011). This allows us to measure oil--and gas--extraction employment, as well as other sectors of interest, more precisely (especially in calculating our energy and industry mix terms).…”

Section: Estimation Approach Variables and Data Sourcesmentioning

confidence: 99%

Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?

Tsvetkova

Partridge

2016

Energy Economics

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The U.S. shale boom has intensified interest in how the expanding oil and gas sector affects local economic performance. Research has produced mixed results and has not compared how energy shocks differ from equal--sized shocks elsewhere in the economy. What emerges is that the estimated impacts of energy development vary by region, empirical methodology, as well as the time horizon that is considered. This paper captures these dimensions to present a more complete picture of energy boomtowns. Utilizing U.S. county data, we estimate the effects of changes in oil and gas extraction employment on total employment growth as well as growth by sector. We compare this to the effects of equal--sized shocks in the rest of the economy to assess whether energy booms are inherently different. The analysis is performed separately for nonmetropolitan and metropolitan counties using instrumental variables. We difference over 1--, 3--, 6--, and 10--year time periods to account for county fixed effects and to assess responses across different time horizons. The results show that in nonmetro counties, energy sector multiplier effects on total county employment first increase up to 6--year horizons and then decline for 10--year horizons. In metro counties, 1--year differences analysis suggests crowding out though the multipliers are insignificant in longer horizons. We also observe positive spillovers to the nontraded goods sector, while spillovers are small or negative for traded goods. Yet, equal--sized shocks in the rest of the economy produce more jobs on average than oil and gas shocks, suggesting that policymakers should seek more diversified development.

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Section: Estimation Approach Variables and Data Sourcesmentioning

confidence: 99%

Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?

Tsvetkova

Partridge

2016

Energy Economics

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“…The data for high-technology employment are from the consulting firm EMSI (EMSI.com), which have been used in a variety of published studies such as Nolan et al (2011) and Fallah et al (forthcoming). The importance is that the definition of high-technology industries is at the four-digit NAICs level, which is not reported by government agencies due to confidentiality reasons.…”

Section: Our Dependent Variables Are Various Measures Of Employment Gmentioning

confidence: 99%

Geography and High-Tech Employment Growth in US Counties‡

Fallah

Partridge

Rickman

2013

Journal of Economic Geography

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Abstract. This paper investigates the role of geography in high-tech employment growth across U.S. counties. The geographic dimensions examined include industry cluster effects, urbanization effects, proximity to a research university, and proximity in the urban hierarchy. Growth is assessed for overall high-tech employment and for employment in various high-tech sub-sectors. Econometric analyses are conducted separately for samples of metropolitan and nonmetropolitan counties. Among our primary findings, we do not find evidence of positive localization or within-industry cluster growth effects, generally finding negative growth effects. We instead find evidence of positive urbanization effects and growth penalties for greater distances from larger urban areas. Universities also appear to play their primary role in creating human capital rather than knowledge spillovers for nearby firms. Quantile regression analysis confirms the absence of within-industry cluster effects and importance of human capital for counties with fast growth in high-tech industries.

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“…Working at a national level, Koo (2005) distilled 20 'occupation clusters' from 661 occupations identified in the Bureau of Labor Statistics's ONET system; he then identified groupings based on the skill requirements of associated jobs and examined growth trends in these clusters in the Cleveland metropolitan area, drawing ominous conclusions about the decline of highknowledge occupations there. Nolan et al (2011) resolved difficulties experienced by early researchers in meaningfully linking industries with occupations by proposing a combined 'occupation cluster/industry cluster' (OCIC) construct. Their OCIC location quotient (OCIC-LQ) enables scholars to identify region-specific occupational concentrations for leading industries-for example, a preponderance of managerial workers within a region's chemicals industry (p. 29) where occupational analysis alone would have yielded separate data about managerial occupations and said little about the industries in which they were concentrated.…”

Section: Occupational Cluster Analysismentioning

confidence: 99%

Human-capital-centred Regionalism in Economic Development: A Case of Analytics Outpacing Institutions?

Wolf-Powers¹

2012

Urban Studies

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Drawing on the case of the Delaware Valley Innovation Network, a regional consortium funded under the US Department of Labor, the paper argues that sophisticated analytical tools developed to facilitate workforce-and occupation-led economic development are running ahead of the institution-building required to put new approaches into practice. There are two main reasons for this. First, tensions persist around the role of the public-sector workforce system in regional development initiatives. Secondly, regional stakeholders disagree about whether 'knowledge economy' investments should include the training of manufacturing, transport and logistics workers. The documentation of regional occupational specialisations, 'talent gap' analyses and the clarification of career pathways are crucial components of human-capital-centred regionalism in economic development. However, best analytical practices are of little use without the institutional capacity to translate analysis into coherent, effective policy.Parallelling a reassertion of regionalist thinking in economic development policy in the 2000s has been an increased emphasis on human capital as a source of innovation and competitive advantage. As a result, human capital has become a focus of economic development analysis and policy. Scholars, many of them funded by the US Economic Development Administration, have developed empirical techniques for investigating regions' occupational profiles and have proposed ways in which knowledge about human capital can be used to devise smarter growth strategies.While scholars and practitioners advocate regionally implemented policy efforts that rest on developing human capital, actual instances of such efforts remain underinvestigated. In the context of human-capital-centred regional economic Laura Wolf-Powers is in the

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Linking Industry and Occupation Clusters in Regional Economic Development

Cited by 37 publications

References 7 publications

Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?

Economics of modern energy boomtowns: Do oil and gas shocks differ from shocks in the rest of the economy?

Geography and High-Tech Employment Growth in US Counties‡

Human-capital-centred Regionalism in Economic Development: A Case of Analytics Outpacing Institutions?

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