Data License

All datasets made available through QuantGov, including files accessible via the bulk CSV download page, are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

Under this license, you are free to:

• Use the data for any purpose, including commercial and internal organizational use

• Share, copy, and redistribute the data in any medium or format

• Adapt, remix, transform, and build upon the data

Provided that you give appropriate attribution to QuantGov as described below.

Code License

Any software, scripts, or code made available by QuantGov (including code hosted on GitHub) is licensed under the MIT License, unless otherwise stated.

Attribution Requirement

Users of QuantGov data must provide attribution in a reasonable manner, without implying endorsement by QuantGov.

See the Attribution Standard below for recommended citation language.

Attribution standard

Please attribute any usage of a dataset to the dataset creators, list the specific version of the dataset (if there are multiple versions), and list the date you accessed the data. All QuantGov data are currently hosted at the Hoover Institution, Stanford CA.

Example dataset attribution:

Source: McLaughlin, Patrick A. State RegData, 2024 Release (dataset). QuantGov, Hoover Institution, Stanford, CA. Accessed: Dec. 16, 2025.

Citations to Relevant Journal Articles, Working Papers, and Documentation

Users are also encouraged to cite relevant QuantGov working papers, journal articles, or documentation where appropriate. If you are using any RegData dataset, it is likely appropriate to cite the paper that started it all is Al-Ubaydli and McLaughlin (2017), which should be cited as something like:

Al-Ubaydli, Omar and Patrick A. McLaughlin. 2017. RegData: A Numerical Database on Industry-Specific Regulations for All United States Industries, 1997-2012. Regulation & Governance, Vol. 11-1, pp. 109-123.

The paper that introduced the machine learning algorithms used to create the industry data in Federal RegData 2.2 and beyond, as well as in all of the State RegData datasets and the RegData Canada datasets, was McLaughlin and Sherouse (2019):

McLaughlin, Patrick A. and Oliver Sherouse. 2019. RegData 2.2: A Panel Dataset on US Federal Regulations. Public Choice, Vol. 180, pp. 43-55.

Any State RegData dataset user should cite the version (if known) or the year of publication of the dataset. Examples of publications using State RegData are: Law and McLaughlin (2022) and Bailey et al. (2021).

Disclaimer

QuantGov data are provided “as is,” without warranty of any kind, express or implied. QuantGov makes no representations regarding the accuracy, completeness, or fitness of the data for any particular purpose.