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Entrepreneurship and economic development in cities

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Abstract

Policy makers have identified the relationship between entrepreneurship and economic development. Yet, little is known about how this relationship varies over time in cities with different market sizes. This study examines the link between entrepreneurship and economic development using a panel of 127 European cities between 1994 and 2009. We found that the immediate economic development impact of new firm start-ups is positive for both small-/medium-size cities and large cities. The relationship is U-shaped for large cities, with the indirect effect taking 7 years, but the indirect effect does not occur in small-/medium-size cities. We offer useful information for policy makers, practitioners, and scholars.

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Notes

  1. Formerly known as a larger urban zone (LUZ).

  2. A regional capital is the main city of a region, e.g., Leicester (main city of Leicestershire), York (main city of Yorkshire), and Palermo (main city of Sicily). For more, see Eurostat (2011).

  3. In 1999, the EU collected data for comparable indicators for 58 European cities. The purpose of this first “Urban Audit” was to test the feasibility of collecting comparable measures of the quality of life in European cities. Over the entire EU (EU-15 at the time), around 480 variables were collected for the 58 largest cities. Therefore, we have only 58 largest cities we were able to include in the sample from the very first period. After completion of the Urban Audit, the Commission decided that there was a clear need to continue and improve this approach of collecting comparable information on urban development. The next data collection waves for Urban Audit data took place in 2003 (for EU-15 cities only) and 2004, respectively, (for the new Member States) and in 2006/2007 (for the EU-27 cities plus cities in Norway, Switzerland, Turkey, and Croatia). We acknowledge a limitation of data as only 127 cities were made available. Having 127 cities in our sample both in EU15 and New member states is adequate; the number of cities and variables available has increased from 58 cities in 1999 to 322 cities in 2011. Although our sample does not capture all 322 cities over time, data collection criteria used by Eurostat and having an almost equal number of cities of various sizes from West and East European countries allow us to consider the data representative for European cities.

  4. Some studies exclude companies below a size threshold, e.g., 10 employees (see Fritsch and Mueller 2004). We include new firms with both fewer than and more than 10 employees.

  5. Previous research indicates the use of either employment rate (employed residents) or unemployment rate (unemployed residents) as a control variable (Fritsch and Storey 2014; Fritsch and Wyrwich 2014b). Due to multicollinearity between the two variables, we use only unemployment rate (see Table 2).

  6. http://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/urban/stateofcities_2010.pdf.

  7. For instance, research center cities line up against the rich literature on universities and research institutions playing a key role in producing creative and human capital (Florida et al. 2008). Research centers and knowledge hub cities rely on higher world integration in knowledge finance, and universities are likely positively associated with economic development and have on average higher economic growth (Saxenian 1994; Audretsch 2003; Acs et al. 2009). Other studies also argued that universities lead to spillover of human capital in cities (Faggian and McCann 2009; Belitski and Korosteleva 2011).

  8. We acknowledge the possibility that including 126 (\(127-1\)) dummy variables associated with each city exploits our degrees of freedom in a sample of 319 observations and may potentially decrease the quality of estimation.

  9. If standardized by national average, this measure would be essentially the same as the measure in Glaeser et al. (1992).

  10. This is not surprising because many large European cities, including capitals, have ports and robust activity associated with transportation and shipping—e.g, Stockholm, Barcelona, Helsinki, Athena, Riga, Copenhagen, London, Lisbon.

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Acknowledgments

We thank Rolf Sternberg, Taylor Aldridge, Stepan Zemtsov, Frank van Oort, Christoph Alfken, Johan Klaesson, Mikaela Backman, and participants in the “Geography of Innovation and Growth” session at the 17th Uddevalla Symposium in Uddevalla, Sweden (June 12–14, 2014).

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Authors and Affiliations

  1. Indiana University, 1315 E. 10th Street, Bloomington, IN, 47405, USA

    David B. Audretsch & Sameeksha Desai

  2. Henley Business School, University of Reading, Whiteknights, Reading, RG6 6UD, UK

    Maksim Belitski

Authors
  1. David B. Audretsch
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  2. Maksim Belitski
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  3. Sameeksha Desai
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Corresponding author

Correspondence to Maksim Belitski.

Appendix

Appendix

See Figs. 1, 2, and 3.

Fig. 1
figure 1

Three effects of new business formation on employment change over time. Source: Based on the results of Fritsch and Mueller (2004, 2008)

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Fig. 2
figure 2

Average new firm start-up rates in European cities, 1994–2009. Source: Authors’ calculations based on UAS data and the spatial information obtained from http://epp.eurostat.ec.europa.eu/portal/page/portal/gisco/popups/references/administrative_units_statistical_units_1. Note: The legend shows range bands of variation in the proportion of new businesses

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Fig. 3
figure 3

Average GDP per capita in PPP in European cities, 1994–2009. Source: Authors’ calculations based on UAS data and the spatial information obtained from http://epp.eurostat.ec.europa.eu/portal/page/portal/gisco/popups/references/administrative_units_statistical_units_1. Note: the legend shows range bands of variation in the GDP per capita in PPP

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Audretsch, D.B., Belitski, M. & Desai, S. Entrepreneurship and economic development in cities. Ann Reg Sci 55, 33–60 (2015). https://doi.org/10.1007/s00168-015-0685-x

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