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The role of agglomerations in the emerging performance and the early development of new establishments: evidence from Germany

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Abstract

This paper analyzes the emerging performance and early development of new establishments considering the role of agglomerations. It creates distinctions between the most commonly observed types of new businesses, namely startups, spinoffs, and new establishments that result from a change in proprietorship. The empirical analysis reveals that new establishments with higher productivity emerge in regions with higher population density, regardless of the foundation type. While at the end of the time period analyzed, new establishments in more densely populated regions still show higher productivity levels than those in less densely populated regions, an agglomeration’s role depends on the foundation type. Indeed, while spinoffs in more densely populated regions tend to reflect the higher productivity levels shown in the first time period, the productivity premium of startups in agglomerations diminishes over time. This analysis emphasizes the relevance of location for the setup and early development of new ventures and, more importantly, the varying role of agglomerations conditioned by the characteristics of new businesses.

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Data availability

The data is held by the Institute of Employment Research and publicly available upon approval of a research project. For details, please see: https://www.iab.de/en/erhebungen/iab-betriebspanel.aspx.

Notes

  1. Rosenthal and Strange (2004) provide a comprehensive review of the literature about agglomeration externalities.

  2. Beaudry and Schiffaunrova (2009) provide a review of the empirical evidence underlying the debate about the Marshall or Jacobs theories. While I acknowledge that agglomeration externalities might be related to Marshall or Jacobs theories, determining whether it is diversity or specialization that plays a major role in the performance of new businesses is beyond the scope of this paper.

  3. NUTS stands for Nomenclature of Units for Territorial Statistics and corresponds to a hierarchical regional classification system subdividing the economic territory of the European Union (EU) into regions at three levels. While the NUTS-1 regions are the national states, the NUTS-3 regions are considerably smaller.

  4. The average number of establishments in the survey is about 15,000 each year. Since I exclude the public sector from the analysis, as well as establishments active in the service sector and construction and keep only manufacturing establishments that are up to 7 years old, and due to missing values for independent variables, the average number of observations in my analysis is 5525 (Table 3).

  5. There are established mechanisms to validate that the same establishment is interviewed in posterior waves. For example, the interviewer receives every year the address of the establishment and the number of employees reported in the previous year. With this information, the interviewer confirms the existence of the establishment and proceeds with the survey (Ellguth et al., 2014).

  6. The entire population of German establishments is contained in the Establishment File of the Federal Employment Agency.

  7. For an overview of such potential problems, see Biege et al. (2013), Bosworth and Triplett (2003), Hulten (2010).

  8. For a detailed description of the data, see Fischer et al. (2009) and Kölling (2000).

  9. This is a common limitation of establishment-level data sets as mentioned by Mueller (2008).

  10. This information is delivered from the following question: “How do you assess to overall technical state of the plant and machinery, furniture and office equipment of this establishment compared to other establishments in the same industry? “1” indicates that the establishment has state-of-the-art equipment. “5” indicates that the equipment is obsolete.

  11. The different figures are generated in Stata. The following manual indicates how the boxplots are generated https://www.stata.com/manuals13/g-2graphbox.pdf.

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Acknowledgements

The author is grateful to the Research Data Center of the Institute for Employment Research (IAB) in Nuremberg, Germany, for hospitality and assistance during research visits. Comments from Alex Coad and Igor Asanov as well as from anonymous referees helped me to considerably improve this paper.

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Research project “Agglomeration economies and the development of new firms” funded by Universidad Espíritu Santo. Guayaquil – Ecuador.

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    Javier Changoluisa

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Table 4 Descriptive statistics
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Table 5 Correlations between variables
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Changoluisa, J. The role of agglomerations in the emerging performance and the early development of new establishments: evidence from Germany. J Evol Econ 33, 837–868 (2023). https://doi.org/10.1007/s00191-023-00823-9

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