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The economic microgeography of diversity and specialization externalities: firm-level evidence from Swedish cities
Blekinge Tekniska Högskola, Fakulteten för teknikvetenskaper, Institutionen för industriell ekonomi.
University of Cambridge, GBR.
Lunds universitet, SWE.
2019 (Engelska)Ingår i: Research Policy, ISSN 0048-7333, E-ISSN 1873-7625Artikel i tidskrift (Refereegranskat) Epub ahead of print
Abstract [en]

We employ finely geo-coded firm-level panel data to assess the long-standing question whether agglomeration economies derive from specialization (within-industry), diversity (between-industry) or overall density. Rather than treating the city as a single unit, we focus our analysis on how the inner industry structures of cities influence firm-level productivity. Our results illustrate the co-existence of several externalities that differ in their spatial distribution and attenuation within cities. First, we find robust positive effects of neighborhood-level specialization on TFP as well as a small effect of diversity at the same fine spatial level. These effects are highly localized and dissipate beyond the immediate within-city neighborhood level. Second, we also find that firms benefit from the overall density of the wider city. The results emphasize the relevance of “opening up” cities to study the workings of their inner organization and support the idea that location in a within-city industry cluster in a diversified and dense city boosts productivity. © 2019

Ort, förlag, år, upplaga, sidor
Elsevier B.V. , 2019.
Nyckelord [en]
Agglomeration economies, Attenuation, Diversity, Externalities, Geocoding, Knowledge spillovers, Productivity, Specialization, Agglomeration, Geo coding, Industrial economics
Nationell ämneskategori
Företagsekonomi
Identifikatorer
URN: urn:nbn:se:bth-17707DOI: 10.1016/j.respol.2019.02.003Scopus ID: 2-s2.0-85061793039OAI: oai:DiVA.org:bth-17707DiVA, id: diva2:1294420
Tillgänglig från: 2019-03-07 Skapad: 2019-03-07 Senast uppdaterad: 2019-03-07Bibliografiskt granskad

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Andersson, Martin

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