A groundbreaking research project analyzing the U.S. regulatory ecosystem through computational analysis of over 165,000 corporate annual reports (Form 10-Ks) filed with the SEC between 1993-2016.

Research Overview

This project conceptualizes the regulatory environment as an “ecosystem” where companies are “organisms” that must adapt to regulatory changes. By analyzing over 4.5 million references to U.S. Federal Acts and Agencies, the research provides empirical evidence for regulatory complexity trends.

Publication

Authors: Michael James Bommarito, Daniel Martin Katz
Published: Journal of Statistical Physics (August 2017)
Paper: Available on arXiv and SSRN

Methodology

Data Collection

Source: SEC EDGAR database via LexPredict
Scope: 34,000+ companies, 165,000+ Form 10-K filings
Timeline: 23 years (1993-2016)
Extracted: 4.5+ million regulatory references

Analysis Framework

“Regulatory bitstring” encoding for each company-year
Network analysis of regulatory similarities
Dimensionality and diversity measurements
Temporal evolution tracking

Key Findings

Increasing Regulatory “Temperature”
- Rise in regulatory energy per filing
- Growing complexity over time
Growing Ecosystem Diversity
- Expanding dimensionality of regulatory space
- Increasing distance between companies’ regulatory profiles
Sector-Specific Patterns
- Identification of regulatory “microclimates”
- Industry-specific adaptation patterns

Technical Implementation

The project employs:

Natural Language Processing for reference extraction
Network visualization of regulatory relationships
Statistical modeling of ecosystem dynamics
Jupyter notebooks for reproducible analysis

Impact

This research:

Provides first large-scale empirical evidence for regulatory complexity claims
Establishes framework for measuring regulatory burden
Enables data-driven policy discussions
Demonstrates computational approaches to legal analysis

Broader Significance

“While individuals across the political, economic, and academic world frequently refer to trends in this regulatory ecosystem, far less attention has been paid to supporting such claims with large-scale, longitudinal data.” This project fills that gap with rigorous empirical analysis.