Endogenous Technological Change, Entrepreneurship and Regional Growth

  • Zoltán J. Ács
Part of the Advances in Spatial Science book series (ADVSPATIAL)


This chapter builds on recent research by Ács and Varga (1999) which looked into the question why some regions grow faster than others.1 In this previous project, three distinct strands of literature were examined, each with a long and distinguished history: New Economic Geography (Krugman 1991b), New Growth Theory (Romer 1990), and the New Economics of Innovation (Nelson 1993a). The aspects investigated were the unit of analysis, how endogenous growth was modelled, and the interactions between the actors and institutions in innovation processes. The authors searched for insights that would help develop a clear analytical framework which integrates economic growth, spatial interdependencies and the creation of new technology as an explicit production process to formulate production-oriented regional policies (Nijkamp and Poot 1997).


Human Capital Innovation System Technological Knowledge Knowledge Spillover Endogenous Growth 
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  1. 1.
    Several books have appeared, simultaneously and independently, trying to identify the underlying processes and interconnections that govern regional innovation (Braczyk, Cooke and Heidenreich 1998; de la Mothe and Pacquet 1999; Ratti, Bramanti and Gordon 1997; DeBresson 1996; Ács 2000). Although these books take different approaches, rely on different methodologies, use different data, and define the unit of analysis differently, they all suggest that there is something fundamental at work at the regional level. While they are all interesting, and illuminate pieces of the regional innovation puzzle, neither singularly, nor in concert, do they answer the bigger question as to why some regions are more innovative than others and therefore grow faster.Google Scholar
  2. 2.
    Jaffe 1989, Ács, Audretsch and Feldman 1991, 1994; Glaeser et al. 1992; Anselin, Varga and Ács 1997, 2000; Varga 1998) and innovation systems (e.g. Saxenian 1994; Braczyk, Cooke and Heidenreich 1998; Fischer and Varga 2000; Oinas and Malecki 1999; Sternberg 1999; Ács 2000).Google Scholar
  3. 3.
    This section draws heavily on Ács and Varga (1999).Google Scholar
  4. 4.
    For such surveys see for example Grossman and Helpman 1991; Helpman 1992; Romer 1994; Barro and Sala-i-Martin 1995; Nijkamp and Poot 1997; Aghion and Howitt 1998.Google Scholar
  5. 5.
    If we are concerned with the regional distribution of A, then regional systems of innovation are the proper unit of analysis.Google Scholar
  6. 6.
    This section draws on work with Catherine Armington at the Center for Economic Studies.Google Scholar
  7. 7.
    The SUSB data and their Longitudinal Pointer File were constructed by Census under contract to the Office of Advocacy of the U.S. Small Business Administration. For their documentation of the SUSB files, see Armington (1998).Google Scholar
  8. 8.
    This file was constructed by the Bureau of the Census from its Statistics of U.S. Business [SUSB] files, which were developed from the economic micro data underlying the County Business Patterns. These annual data were linked using the Longitudinal Pointer File, which facilitates tracking establishments over time, even when they change ownership and identification number.Google Scholar
  9. 9.
    For evidence on regional variation on new firm formation see Armington and Ács (2000).Google Scholar
  10. 10.
    The LEEM data cover all private sector businesses with employees, with the exception of those in agricultural production, railroads, and private households. This is the same universe covered in the annual County Business Patterns publications, but establishments with a positive payroll during a year but no employment in March of the same year are not counted for that year.Google Scholar
  11. 11.
    There is a small number [ 10,000 to 16,000] of new firms each year for which no industry code is ever available. Most of these are small and short-lived. These have been added to the local market category, which is by far the largest of our sectors.Google Scholar
  12. 12.
    A fourth implication of the New Growth Theory is that given the fixed and finite costs of new discoveries, the larger the size of the market the faster the rate of growth. Therefore, tapping into unexplored domestic markets and into foreign markets for trade can raise the rate of growth by boosting the incentive for technological discovery and therefore boost output itself (Ács and Morck 1999).Google Scholar
  13. 13.
    The complete study [The State of the Incubator Industry] can be downloaded from the web at Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Zoltán J. Ács
    • 1
  1. 1.Robert G. Merrick School of Business, Department of Economics and FinanceUniversity of BaltimoreUSA

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