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Agglomeration externalities, market structure and employment growth in high-tech industries: Revisiting the evidence

Author

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  • Cieślik Andrzej

    (Department of Macroeconomics and International Trade Theory, Faculty of Economic Sciences, University of Warsaw Poland)

  • Ghodsi Mahdi

    (The Vienna Institute for International Economic Studies, Austria)

Abstract

In this paper we revisit the existing empirical evidence on the effects of various agglomeration externalities and the market structure on employment growth in the high-tech industries of the European Economic Area (EEA). Our study is based on the dynamic panel dataset of two-digit NACE rev 1.1. industries in 285 regions of the European Economic Area for the period 1995-2007. We find that employment growth is negatively related to competition, while localization and urbanization externalities do not seem to affect growth.

Suggested Citation

  • Cieślik Andrzej & Ghodsi Mahdi, 2015. "Agglomeration externalities, market structure and employment growth in high-tech industries: Revisiting the evidence," Miscellanea Geographica. Regional Studies on Development, Sciendo, vol. 19(3), pages 76-81, September.
    • Handle: RePEc:vrs:mgrsod:v:19:y:2015:i:3:p:76-81:n:1
    DOI: 10.1515/mgrsd-2015-0007
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    Cited by:

    1. Carlos Carreira & Luís Lopes, 2020. "How are the potential gains from economic activity transmitted to the labour factor: more employment or more wages? Evidence from the Portuguese context," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(2), pages 319-348, April.
    2. Weiliang Chen & Xinjian Huang & Yanhong Liu & Xin Luan & Yan Song, 2019. "The Impact of High-Tech Industry Agglomeration on Green Economy Efficiency—Evidence from the Yangtze River Economic Belt," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    3. Hu, Lirong & He, Shenjing & Han, Zixuan & Xiao, He & Su, Shiliang & Weng, Min & Cai, Zhongliang, 2019. "Monitoring housing rental prices based on social media:An integrated approach of machine-learning algorithms and hedonic modeling to inform equitable housing policies," Land Use Policy, Elsevier, vol. 82(C), pages 657-673.

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