Scholars discuss how wealthy interest groups influence agency rulemaking.
With federal agencies shaping nearly every aspect of our lives, wealthy interest groups are pouring money and resources into the public comment process to influence agency rulemaking. Yet, despite this mounting pressure from interest groups, research on the true impact of their comments on final rules has been sparse.
Recent research by Daniel P. Carpenter—Allie S. Freed Professor of Government and Chair of the Department of Government at Harvard University—and other leading scholars changes that.
In their recent report, the researchers analyze a new dataset of over 260,000 public comments on proposed regulations following the 2008 financial crisis. Carpenter and his coauthors find that wealthier organizations are more likely to not only participate in administrative policymaking, but also have their concerns addressed. According to the Carpenter team, these results suggest that inequality in the notice-and-comment process “runs much deeper than previously appreciated.”
Their research breaks ground as the first large-scale examination of wealth inequality in agency rulemaking.
Past research on economic inequality in policymaking had demonstrated a bias toward wealthy parties. These studies, however, focused predominantly on legislative lawmaking. Carpenter and his coauthors theorized that similar forces of wealth inequality are at play in the federal agency notice-and-comment process.
The Administrative Procedure Act of 1946 requires federal agencies to notify the public of a proposed regulation, invite public comments, and consider comments received before the agency finalizes it. Since an agency may modify its proposed regulation based on public comments, interested persons often invest considerable resources in the comment process to influence a final regulation.
In light of this notice-and-comment process, Carpenter and his coauthors hypothesized that agency rulemaking “presents a unique opportunity to study the relationship between organizational wealth and policy influence.”
To test their theory, Carpenter and his coauthors analyzed agency regulations implementing the Dodd-Frank Wall Street Reform and Consumer Protection Act of 2010 (Dodd-Frank). The researchers chose to focus on Dodd-Frank rulemaking for two reasons.
First, Carpenter and his coauthors were drawn to the breadth of the agency action under Dodd-Frank. Following the 2008 financial crisis, Congress delegated significant authority to federal agencies to implement Dodd-Frank. Given this massive allocation of regulatory power, the researchers’ dataset spanned over 800 actions across seven agencies.
Second, the researchers were drawn to the high stakes of Dodd Frank regulations. Through their Dodd-Frank rulemaking, agencies sought to alter the financial system by, for example, stabilizing important banks and improving consumer protection. Given the vast amount of money at stake, banks and other interested groups spent hundreds of millions of dollars to try to change the regulations in their favor.
To assess wealth inequality within Dodd-Frank rulemaking, Carpenter and his coauthors compiled data on public comments, the proposed versus final regulations, and commenting organizations’ wealth, political spending, and lobbying efforts.
After analyzing the data, the researchers offer five takeaways about the relationship between organizational wealth and policy influence in agency rulemaking.
First, Carpenter and his coauthors find that wealthier organizations engage in agency rulemaking more frequently than less wealthy counterparts. Both within and across different types of organizations, the researchers point out, wealthier organizations have “a disproportionate voice in policymaking.”
Second, the researchers demonstrate that “for-profit banks are more likely to participate than non-profit banks.” These results, Carpenter and his coauthors contend, stand even when controlling for differences in organizational assets.
Third, the Carpenter team show that organizations that commented on Dodd-Frank rules also donated more to political campaigns through Political Action Committees (PACs). Among organizations that donate to PACs, the researchers find, the average two-year campaign spending for organizations that commented on a Dodd-Frank regulation was $85,000, compared to only $54,000 for organizations that did not comment.
Fourth, the researchers suggest that wealthier organizations submit comments that are more technically and legally sophisticated than those of less wealthy organizations. Their data reflected that the commenting companies valued over $10 billion submitted comments with around 1,000 technical terms, while smaller companies’ comments contained only 100 technical terms on average.
Finally, Carpenter and his coauthors find that agencies are more likely to incorporate text from the comments of wealthier organizations than from the comments of less wealthy organizations. For each legal citation in a comment, about 14 additional words from the comment are included in the final rule.
When analyzing these trends, Carpenter and his coauthors conclude that lobbying sophistication explains much of the bias in agency rulemaking. The researchers reason that “money buys technical and legal sophistication, and sophistication appears to buy changes to policy documents.”
These results, Carpenter and his coauthors argue, suggest the inequality in the agency rulemaking process runs deep. Even when isolating for only wealthy organizations, the researchers point out, those with the most financial resources have an even stronger advantage.
The Carpenter team also addresses the implications of its findings on policy reforms. It recommends efforts that target the unequal access to legal and technical expertise. Reforms that provide legal assistance or subsidies to commenting organizations with less resources, according to the researchers, may prove effective.
Although more research is needed, Carpenter and his coauthors conclude that their findings suggest such reforms to “level the playing field between differentially resourced groups” merits future study.
