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Regional Innovative Capacity with Endogenous Employment: Empirical Evidence from the U.S

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Author Info

  • Riddel, Mary

    (Center for Business and Econ Research, U NV, Las Vegas)

  • Schwer, R. Keith

    (Center for Business and Econ Research, U NV, Las Vegas)

Abstract

Using the endogenous growth model proposed by Romer (1990) and operationalized by Stern, Porter, and Furman (2000), we seek to identify factors that affect innovative capacity in the U.S. We find strong evidence of endogeneity between employment growth and innovative capacity. In response, we estimate a generalized two-stage random effects model of hi-tech employment and patenting activity. We find that the stock of knowledge (standing on shoulders effect), industry R&D expenditures, and the number of high-tech employees explain the rate of change of innovation among the states during the 1990s. The stock of human capital also influences the innovation rate. Our findings suggest that patenting activity and wages in the high-tech sector are the primary forces influencing the demand for high-tech labor.

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Bibliographic Info

Article provided by Southern Regional Science Association in its journal Review of Regional Studies.

Volume (Year): 33 (2003)
Issue (Month): 1 ()
Pages: 73-84

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Handle: RePEc:rre:publsh:v:33:y:2003:i:1:p:73-84

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Web page: http://www.srsa.org

Related research

Keywords: R&D; Regional;

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Cited by:
  1. Brown, Stephen P. A. & Hayes, Kathy J. & Taylor, Lori L., 2003. "State and Local Policy, Factor Markets, and Regional Growth," The Review of Regional Studies, Southern Regional Science Association, vol. 33(1), pages 40-60.
  2. Laura de Dominicis & Raymond J.G.M. Florax & Henri L.F. de Groot, 2013. "Regional clusters of innovative activity in Europe: are social capital and geographical proximity key determinants?," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2325-2335, June.
  3. Robert Huggins & Andrew Johnston & Rebecca Steffenson, 2008. "Universities, knowledge networks and regional policy," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 1(2), pages 321-340.
  4. Jose M. Pastor & Juan Fernández de Guevara & Francisco Pérez, 2010. "Measuring the local economic impact of universities: an approach that considers uncertainty," Investigaciones de Economía de la Educación volume 5, in: María Jesús Mancebón-Torrubia & Domingo P. Ximénez-de-Embún & José María Gómez-Sancho & Greg (ed.), Investigaciones de Economía de la Educación 5, edition 1, volume 5, chapter 54, pages 1061-1090 Asociación de Economía de la Educación.
  5. David L. Barkley & Mark S. Henry & Doohee Lee, 2006. "Innovative activity in rural areas: the importance of local and regional characteristics," Community Development Investment Review, Federal Reserve Bank of San Francisco, pages 1-14.
  6. Laura de Dominicis & Raymond J.G.M. Florax & Henri L.F. de Groot, 2011. "Regional Clusters of Innovative Activity in Europe: Are Social Capital and Geographical Proximity the Key Determinants?," Tinbergen Institute Discussion Papers 11-009/3, Tinbergen Institute.
  7. Breand�n � hUallach�in & Timothy F. Leslie, 2007. "Rethinking the regional knowledge production function," Journal of Economic Geography, Oxford University Press, vol. 7(6), pages 737-752, November.
  8. Andrés Rodríguez-Pose & Marco Di-Cataldo, 2014. "Quality of government and innovative performance in the regions of Europe," Papers in Evolutionary Economic Geography (PEEG) 1406, Utrecht University, Section of Economic Geography, revised Feb 2014.
  9. Barkley, David L. & Henry, Mark S. & Lee, DooHee, 2006. "Innovative Activity in Rural Areas: The Role of Local and Regional Characteristics," REDRL Research Reports 113802, Clemson University, Regional Economic Development Research Laboratory (REDRL).
  10. Fernandes, Cristina & Ferreira, João, 2011. "Knowledge Spillovers and Knowledge Intensive Business Services: An Empirical Study," MPRA Paper 34751, University Library of Munich, Germany.

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