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Gauging Metropolitan “High-Tech†and “I-Tech†Activity

Author

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  • Karen Chapple
  • Ann Markusen
  • Greg Schrock
  • Daisaku Yamamoto
  • Pingkang Yu

Abstract

In the past few years, a number of new studies have published high-tech rankings of American metropolitan areas that are used by many business consultants and local economic development organizations to advise firms on location strategies. In this article, the authors generate their own rankings based on an occupational definition of “high techness†and compare them with those of four other studies. The results rank larger and older industrial cities, such as Chicago, New York, and even Detroit, higher than many of the smaller places celebrated as high tech, such as Austin. The work demonstrates that the methodology underlying rankings is crucially important to the outcome. By abandoning narrow notions of high tech restricted to maturing technologies in computers, electronics, and telecommunications and instead using science and technology (S&T) occupations as a marker for high tech, it may be possible to tag the innovative potential of emerging sectors, including high-tech services.

Suggested Citation

  • Karen Chapple & Ann Markusen & Greg Schrock & Daisaku Yamamoto & Pingkang Yu, 2004. "Gauging Metropolitan “High-Tech†and “I-Tech†Activity," Economic Development Quarterly, , vol. 18(1), pages 10-29, February.
    • Handle: RePEc:sae:ecdequ:v:18:y:2004:i:1:p:10-29
    DOI: 10.1177/0891242403257948
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    Cited by:

    1. Giovanni Dosi & Emanuele Pugliese & Pietro Santoleri, 2017. "Growth and survival of the `fitter'? Evidence from US new-born firms," LEM Papers Series 2017/06, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Shahid Yusuf, 2012. "From Technological Catch-up to Innovation : The Future of China’s GDP Growth," World Bank Publications - Reports 12781, The World Bank Group.
    3. Elsie Echeverri‐Carroll & Sofia G. Ayala, 2009. "Wage differentials and the spatial concentration of high‐technology industries," Papers in Regional Science, Wiley Blackwell, vol. 88(3), pages 623-641, August.
    4. Yusuf, Shahid, 2007. "From creativity to innovation," Policy Research Working Paper Series 4262, The World Bank.
    5. Echeverri-Carroll, Elsie L. & Oden, Michael D. & Gibson, David V. & Johnston, Evan A., 2018. "Unintended consequences on gender diversity of high-tech growth and labor market polarization," Research Policy, Elsevier, vol. 47(1), pages 209-217.
    6. Meir Russ & Gaurav Bansal & Adam Parrillo, 2017. "The “Knowledge City” and the “Experience City”: the Main, Mediating, and Moderating Effects of Education on Income and Economic Inequality," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(3), pages 804-829, September.
    7. Maria Kokoreva & Anastasia Stepanova & Kirill Povk, 2017. "Could High-Tech Companies Learn from Others While Choosing Capital Structure?," HSE Working papers WP BRP 62/FE/2017, National Research University Higher School of Economics.
    8. Ari-Veikko Anttiroiko, 2015. "City Branding as a Response to Global Intercity Competition," Growth and Change, Wiley Blackwell, vol. 46(2), pages 233-252, June.

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