Is Dodd-Frank the Biggest Law Ever?

July 20, 2020

The Dodd-Frank Wall Street Reform and Consumer Protection Act (commonly known as Dodd-Frank), which was intended to address perceived problems in the financial system and prevent future crises, is the biggest act of Con­gress in recent history, in terms of the volume of regulations resulting from it. The sheer size and complexity of the 2010 law can undermine the quality of the regulations that the law authorizes. In “Is Dodd-Frank the Biggest Law Ever?” Patrick A. McLaughlin, Oliver Sherouse, Mark Febrizio, and M. Scott King develop new methods for empir­ically assessing the size, scope, and complexity of laws and use those methods to analyze Dodd-Frank.

Size and Complexity Can Undermine Effectiveness

Dodd-Frank is part of a general trend toward longer and more complex laws in the United States. For at least three reasons, its status as the “biggest law ever” could make achieving its stated outcomes more difficult.

  1. Congress cannot adequately anticipate the actual effects of large laws such as Dodd-Frank. Because their time was scarce, members of Congress were unlikely to thoroughly understand the complexity and con­sequences of Dodd-Frank when it was being debated. This is often the case with bills that are voted on during times of perceived crisis.
  2. Laws such as Dodd-Frank create a surge in the output of regulations. It has been estimated that Dodd-Frank increased regulatory restrictions for the financial industry by 32 percent, which is more than the increase in restrictions from 1997 to 2010. Such a large volume of new rules can overwhelm the already-capacity-constrained quality control process. Unintended consequences can result, especially because policymakers have less time and resources to analyze individual components of laws.
  3. A large act can precipitate the creation of many regulations by different agencies that target the same industry. When multiple agencies simultaneously develop rules affecting a particular industry, the interactions between those rules are difficult to know at best and completely unconsidered at worst. Furthermore, the longevity of congressional mandates suggests that any problems created by Dodd-Frank will perpetually guide regulatory agency rulings. For example, the act gave the new Consumer Financial Protection Bureau an organizational structure that leaves it insulated from congressional and judicial oversight.

Key Takeaway

The length and complexity of financial laws such as Dodd-Frank is concerning because it can lead to the creation of lower-quality regulations. These negative effects will likely be long lived, since (a) Congress does not regularly modify statutes that cause poor regulation and (b) members do not usually possess the context-specific knowledge to evaluate which pieces of legislation are the source of substandard rules.

Performance Standards vs. Design Standards: Facilitating a Shift toward Best Practices

June 26, 2019

Performance standards are generally accepted as a best practice in regulatory rulemaking. Yet agencies often default to design standards instead. In “Performance Standards vs. Design Standards: Facilitating a Shift toward Best Practices,” Laura Montgomery, Patrick McLaughlin, Tyler Richards, and Mark Febrizio examine the advantages of performance standards over design standards. They also consider the drawbacks of performance standards and how those drawbacks can be overcome.

A performance standard establishes a goal that regulated entities must achieve. It is often characterized by a threshold above or below which the entity must remain. In the automobile industry, for example, this type of standard could include a specific emission standard a vehicle must meet.

A design standard, on the other hand, mandates that regulated entities employ a particular means of compliance. For example, a design standard may require vehicles to be equipped with a specific type of catalytic converter to reduce emissions. The difference between the two is that performance standards allow the entity to meet the standard in whatever way it chooses (within the constraints of the law), while design standards mandate the approach it must take to meet the standard.

Benefits of Performance Standards Relative to Design Standards

  • They permit regulated entities to choose the approach best suited to their situation. Firms are better placed than regulators to determine what processes and actions are required within their businesses to achieve a given regulatory objective. Design standards choose the compliance technology for all businesses.
  • They allow for innovation and entrepreneurship in compliance. Design standards often discourage or even outlaw such activity.
  • They help ensure a fair playing field for regulated entities. When properly crafted, performance standards can help mitigate government favoritism and reduce disproportionate burdens from regulation.

Drawbacks of Performance Standards—and How to Overcome Them

Reluctance to adopt performance standards is often a result of the uncertainty, greater risk, and measurement challenges they can bring. Agencies also do not always make clear what must be done to achieve or satisfy the standard. With design standards, regulated entities may be confident that, so long as they implement the design, they will be in compliance.

There are several steps that agencies can take to ensure effective implementation of new performance standards:

  • Set standards that are reasonable and attainable
  • Focus the requirements on the ends, not the means
  • Make the requirements clear and simple so that regulated entities know what they must do to comply
  • Evaluate measurement costs for agencies and compliance costs for regulated entities
  • Lay out a clear plan for compliance testing and enforcement
  • Consider how a regulation might disproportionately harm small businesses or low-income households
  • Consider large penalties for misconduct when the likelihood or cost of fraud or evasive behavior is high
  • Consider potential unintended consequences, such as what kind of tradeoffs regulated entities might make following a new regulation.

Learning from Other Agencies

Agencies can learn from the actions and experiences of other agencies that have adopted performance standards. For example, a key benefit of the Federal Aviation Administration’s performance-based approach is that the means of compliance are adaptable over time, able to adjust to changing market conditions and technology

Similarly, the Federal Railroad Administration is currently reforming its regulatory approach by amending its passenger safety requirements to improve compatibility with advanced technologies such as high-speed rail. By creating more flexibility, the new approach allows firms to meet requirements in the most cost-effective way.

Mapping Regulatory Restrictions in US States

February 26, 2019

Data show that regulatory accumulation has occurred for decades in the United States at the federal level, but knowledge is limited regarding how much regulation exists among US states. State RegData—a product built on the QuantGov platform—offers a starting point for tracking and comparing regulation and its trends at the state level.

State RegData quantifies regulatory restrictions, which are words and phrases that indicate legal obligations or prohibitions in state administrative codes. Specifically, the dataset counts instances of the words shall, must, may not, required, and prohibited. To assess how relevant a restriction is to an industry, State RegData uses machine learning algorithms to connect regulatory restrictions to industries and sectors of the economy, as defined by the North American Industry Classification System (NAICS).

At the time of this writing, State RegData includes data on 27 states with more in development. Unsurprisingly, State RegData reports significant variety in the amount of regulation among states. New York, the most regulated state in the dataset, has 307,636 restrictions in its administrative code. Illinois, Ohio, and Texas all have more than 200,000 regulatory restrictions. At the other end of the spectrum, Arizona’s regulatory burden is merely 63,919 restrictions. Connecticut, Michigan, Minnesota, and Utah also have fewer than 100,000 restrictions in their administrative codes. Below is a graphical presentation of the current number of regulatory restrictions (in thousands) across the United States.

In one sense, the amount of regulation is not necessarily good or bad. More regulation could reflect a larger population or the presence of industries that may require a greater amount of oversight. Additionally, State RegData weights each restrictive term equally and does not distinguish whether specific restrictions are more burdensome than others.

Nevertheless, regulation is a tool that affects economic outcomes. As the amount of regulation increases, the volume of duplicative or obsolete rules is also likely to grow. Furthermore, regulations can create unintended consequences or have unpredictable interactive effects.

State RegData permits researchers to compare regulatory burdens among states and identify economic trends and relationships. Such information can inform policymakers about the economic effects of regulation and improve regulatory decision-making.

Comparing Regulations across US States

August 7, 2018

Regulatory economists often focus their research on regulations originating from the federal government. Even for analyses of US states, they frequently focus on broad indices that attempt to measure the regulatory climate across states or the varying impact of federal rules on different states. More recently, however, State RegData—a database built on the QuantGov platform—gives researchers and policymakers the ability to conduct industry-specific analysis of state-level regulatory restrictions.

Extending the logic of the RegData project to US states, State RegData converts regulatory text in state administrative codes into datasets containing statistics about those regulations, such as restriction counts, word counts, and industry relevance. State RegData adopts the RegData methodology of using text analysis to quantify words and phrases that typically signify legal prohibitions or obligations in regulatory text—specifically, shall, must, may not, prohibited, and required. The project also uses machine learning algorithms to assess the probability that restriction counts are relevant to specific industries. The RegData project’s approach is more fully explained here.

The quantification of regulatory restrictions permits comparisons across states. Since every dataset must be uniquely developed for each state administrative code, the scope of State RegData is still expanding, with 24 states currently represented as a cross section. So far, New York has the most regulatory restrictions in its administrative code, with more than 300,000 restrictions, while Arizona has the least, with fewer than 65,000 restrictions on the books. The majority of states fall between 100,000 and 200,000 restrictions. By comparison, there were about 1.08 million regulatory restrictions in federal regulations in effect at the end of 2017, which means that states on average appear to have roughly 10 to 20 percent the number of regulatory restrictions as the federal government.Furthermore, it is not merely total regulations at the state level that matter but also which industries are affected. Determining the best way to assess the regulatory burden on an industry has its challenges. First, cumulative measures have a problem with double-counting, since significant overlap in the types of regulations that states adopt is likely. Many businesses only operate in a single state, and even businesses operating in multiple states do not necessarily have a drastically higher burden if rules are relatively similar. Second, mean numbers of restrictions could be biased by outliers if certain states have unusually regulated (or unregulated) sectors. Using median restriction counts mitigates both issues.

State RegData identifies industries by using the 2007 version of the North American Industry Classification System (NAICS) at the three-digit level. Unsurprisingly, the top 10 median industry-relevant restriction counts are concentrated in sectors such as medical services, manufacturing, and utilities. The most regulated sector is ambulatory healthcare services (NAICS code 621), with a median of about 5,000 restrictions.This database provides information that is quite distinctive from that of federal RegData. Federal agencies and state governments have different jurisdictions and priorities, and the most regulated industries at the federal and state levels often depend on specific legislation (e.g., Dodd-Frank). While the impact of federal regulation on states varies, that is due to variation in the makeup of state economies rather than different amounts of regulation. Conversely, state regulatory texts exhibit vast differences in what sectors they regulate most stringently. For example, the utilities sector (NAICS code 221) has the most industry-relevant restrictions for Missouri, North Carolina, and Wisconsin but does not appear in the top 10 targeted industries for Connecticut, Maryland, or Nebraska.

State RegData will eventually cover as many of the states as possible. When State RegData is used in conjunction with data on federal regulations from RegData, researchers will have the opportunity to work with comprehensive data that use a consistent and comparable metric across time, place, and industry.