Measuring and Modeling the U.S. Regulatory Ecosystem

In December 2016, we published the first large-scale, longitudinal summary of regulatory growth entitled Measuring and Modeling the U.S. Regulatory Ecosystem. In this research paper, we demonstrate that SEC-listed companies have experienced a four-fold increase in the rate at which they cite regulatory exposure. Unlike other studies based solely on number of bills or pages of regulation, these measures provide a much more realistic picture of experienced regulatory growth.

You can find more coverage of this research in Quartz here: The rate at which US companies cite regulations as an obstacle has quadrupled over the last 20 years

Measuring and Modeling the U.S. Regulatory Ecosystem


Over the last 23 years, the U.S. Securities and Exchange Commission has required over 34,000 companies to file over 165,000 annual reports. These reports, the so-called “Form 10-Ks,” contain a characterization of a company’s financial performance and its risks, including the regulatory environment in which a company operates. In this paper, we analyze over 4.5 million references to U.S. Federal Acts and Agencies contained within these reports to build a mean-field measurement of temperature and diversity in this regulatory ecosystem. While individuals across the political, economic, and academic world frequently refer to trends in this regulatory ecosystem, there has been far less attention paid to supporting such claims with large-scale, longitudinal data. In this paper, we document an increase in the regulatory energy per filing, i.e., a warming “temperature.” We also find that the diversity of the regulatory ecosystem has been increasing over the past two decades, as measured by the dimensionality of the regulatory space and distance between the “regulatory bitstrings” of companies. This measurement framework and its ongoing application contribute an important step towards improving academic and policy discussions around legal complexity and regulatory growth.

Read the paper on SSRN here