The purpose of this paper is to discuss new findings on municipal-level occupational licensing and other forms of regulation and introduce a new data set available for researchers to study this largely unexplored area.
Municipal occupational regulatory data were gathered in 2017 and 2018 from the 50 largest cities in the USA. Data available in the data set include city and state IDs, occupational IDs, requirements associated with the regulations (e.g. education, experience and fees), penalties for practicing without meeting the requirements, regulatory type and NAICS category. Descriptive statistics are used to present information about the number and types of occupations regulated and the number and types of regulations present in the cities.
The median number of occupations regulated by a city is 24.5, but the numbers per city vary substantially. The 1,832 occupations in the data set are distributed across every NAICS category. The most prevalent form of regulation is registration; certification is least used. Cities are quite diverse in the types of regulations applied to occupations, and the type of regulation varies substantially by industry type.
Research on licensing is dominated by state-level analyses. Largely absent are systematic analyses of licensing and other regulation at the municipal level, likely due to a lack of data. This means the current licensing literature underestimates – perhaps severely so – the prevalence, burdens and effects of licensing. The data introduced and discussed in this paper can help remedy this dearth of municipal licensing analyses.
This paper forms part of a special section “Occupational Licensing and Entrepreneurship”, guest edited by Edward J. Timmons.
The authors thank the attorneys at the Skadden, Arps, Slate, Meagher and Flom law firm for many pro bono hours spent gathering the data described in this paper.
Carpenter, D., Sweetland, K., Vargo, E. and Bayne, E. (2021), "Introducing a new data set on municipal-level occupational regulation", Journal of Entrepreneurship and Public Policy, Vol. 10 No. 2, pp. 143-155. https://doi.org/10.1108/JEPP-08-2019-0064
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