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How does municipal governance structure affect innovation and knowledge diffusion? Evidence from U.S. metro areas

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Abstract

As declining state and federal aid forces regional governments to become more self-reliant, there is new interest in understanding factors that support regional resilience to economic and natural disasters. Using a sample of 365 metropolitan statistical areas, we examine one such factor: how regional government fragmentation shapes patented innovation, a known mechanism for bolstering resilience. While we find no evidence that the number of general-purpose governments (per capita) impact regional innovation, we do find that regions with a higher density of special-purpose governments have less inclusive innovation. This is true in terms both of who does the inventing and what is invented. Previous research links higher numbers of special-purpose government units to weaker economic performance; our results suggest higher numbers may also hinder regions’ abilities to adapt to disruptions.

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Notes

  1. An often cited criticism of polycentric governance is that it can lead to urban sprawl. See Carruthers and Ulfarsson (2003) for an overview of this work.

  2. The polycentricity approach to municipal governance is far more nuanced than we can address in this paper. See Aligica and Tarko (2012) for a more thorough discussion of the key principles and historical foundations.

  3. A patent’s assignee is the individual or organization that owns the legal property right to the patent. Patents are assigned to MSAs based on the residence of the inventor(s) and are fractionally weighted by the number of co-inventors. Patents where the primary product/technology class is design or plant are excluded.

  4. The Census Bureau’s Annual Survey of Government Finance relies on a much smaller sample of governments. For instance, the 2001 annual survey sampled 19,685 governments, of which 68.5% were school districts, 14.6% were special districts, 6.9% were counties, 5.9% were cities, and 3.6% were townships. Because the annual surveys significantly over-represent school districts and under-represent special districts, relying on their data to measure fragmentation would likely be misleading. The survey methodology for the Census of Governments may be found here: https://www.census.gov/programs-surveys/cog/technical-documentation/methodology.html[accessed: 11/2/2021].

  5. If one were to use a two-way fixed effects framework, the inclusion of MSA-specific fixed effects would remove all the cross-sectional variation in the data. In this case, the coefficients would be identified from within-MSA variation over time.

  6. The Census Bureau’s definition of STEM occupations are available at the following URL: https://www2.census.gov/programs-surveys/demo/guidance/industry-occupation/stem-census-2010-occ-code-list.xls[Accessed: 12/8/2018].

  7. The BLS industry-occupation crosswalks by industry are available at the following URL: https://www.bls.gov/emp/tables/industry-occupation-matrix-industry.htm[Accessed: 12/8/2018].

  8. The economic freedom index varies from 0 (least free) to 10 (most free) and is the average of scores given to three broad areas of governance: (1) spending; (2) taxation; and (3) labor market freedom. See Stansel (2019) for more details.

  9. Using the NBER patent subcategories, agricultural patents are category 11 and health care patents are categories 31 and 32.

  10. The Census of Governments provides counts of the number of governmental units, by county, dating back to 1942. However, the first year that detailed financial data are provided by governmental unit is 1972.

  11. The number of churches by denomination is provided at the county level in the Survey of Churches and Church Membership. All the empirical variables used in this paper, including our HHI church measure, use the 2015 MSA definitions from the Office of Management and Budget when aggregating county-level data is required.

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Authors and Affiliations

  1. Acadiana Business Economist Endowed Chair, Economics, University of Louisiana at Lafayette, Lafayette, USA

    Gary A. Wagner

  2. Old Dominion University, Norfolk, USA

    Timothy M. Komarek

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  1. Gary A. Wagner
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Correspondence to Gary A. Wagner.

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We thank two anonymous referees and seminar participants from the Crises and Community Resilience workshop hosted by the University of North Texas’s Economics Research Group and West Virginia University’s Center for Free Enterprise for valuable feedback. Any errors are our own.

Appendix

Appendix

Table 9 First-stage regression results
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Wagner, G.A., Komarek, T.M. How does municipal governance structure affect innovation and knowledge diffusion? Evidence from U.S. metro areas. Econ Gov 24, 287–330 (2023). https://doi.org/10.1007/s10101-022-00286-x

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