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Patrick A. McLaughlin

There’s hope for pruning federal regulations. Some state experiments are paying off

A worker atop a home under construction
A worker atop a home under construction in Irvine in 2021.
(Allen J. Schaben / Los Angeles Times)

President Trump’s One Big Beautiful Bill Act includes $100 million for the Office of Management and Budget “to pay expenses associated with improving regulatory processes and analyzing and reviewing rules.” Following the Department of Government Efficiency initiative, this small investment won’t make many headlines — but it should. If that money is put to use in the way several states have done to reduce built-up red tape, the return on investment will make even the crankiest budget hawk crack a smile.

A recent Council of Economic Advisers report found that just a modest portion of the president’s deregulatory agenda could save the nation some $907 billion. Californians, who live in America’s most-regulated state, understand these costs better than most.

Take housing, for example. California’s thriving economy and broad appeal are a recipe for expensive homes, but its famously stringent building and other restrictions create something else: enough scarcity to propel home prices to around 2.5 times the national median. The costs extend further than the sticker price. They make it harder to rebuild after a natural disaster. They send workers and employers fleeing for other states or far-flung areas. They keep young people from finding their way to Westwood, Berkeley or Silicon Valley for better futures.

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All of this adds up, and it’s about more than a handful of “good” or “bad” regulations. It’s about moving too slowly to streamline an entire system that fails millions of people. Federal officials now have resources and a mandate to identify failures in the federal code — the question is “how?”

The answer is taking shape. Federal officials can look at a specific playbook that’s getting results in nearby Richmond, Va. Shortly after taking office in 2022, Virginia Gov. Glenn Youngkin issued an executive order setting the ambitious goal of cutting regulatory requirements by 25% by the end of his term. As of this month, his administration has hit the target, and Virginia’s Office of Regulatory Management anticipates cutting nearly 33% — and 50% of the words in related guidance documents — by the end of his term.

These numbers are not smoke and mirrors or budgeting gimmicks. Virginia painstakingly and comprehensively inventoried its regulations, including third-party standards that are referenced (which therefore become regulations, too) and guidance documents. Every change has been meticulously and transparently cataloged on the state’s regulatory town hall website.

And what’s the return on investment? So far, it’s saving Virginia businesses and citizens more than $1.2 billion per year.

From reducing the number of training hours required to earn a living as a licensed cosmetologist to streamlining housing regulations (estimated to shave $24,000 off the construction cost of a new house and enable construction professionals to work much faster), working people are coming out ahead.

Virginia is showing Washington that substantial regulatory reform can be accomplished on a shoestring budget. The office that was stood up to oversee the reforms — the Office of Regulatory Management — consists of only four dedicated employees: a director, a deputy director and two policy analysts. Going forward, artificial intelligence will further reduce the costs of cataloguing and processing untold amounts of regulatory requirements.

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The technology is a perfect fit for regulatory text. It can process thousands of pages in a tiny fraction of the time it takes a person — and given the hundreds of thousands of pages of such text on the books in Washington, investing in AI-driven regulatory review tech should be a top priority for that $100-million budget.

The White House can also learn from Virginia’s specific application of AI. The state is undertaking a pilot program with at least two separate approaches.

First, its AI tool will scan both statutory and regulatory codes side by side and identify the regulatory requirements that go beyond the minimum laid out by statute. Many of these “discretionary” requirements may still prove necessary to protect public health and safety, but some will not. A human being will then look at the mismatches and examine which regulations to consider scaling back.

Second, the tool will compare each government agency’s regulatory code against the corresponding codes of other states. A human being will again review the results and identify instances in which Virginia regulation is needlessly stricter than that of other states.

For example, the algorithm might flag that Virginia requires professional masseurs to undergo 500 hours of training, while the least restrictive state requires only 300 hours. Absent evidence that the other state produces subpar or unsafe practitioners, Virginia officials might decide the 500-hour requirement is too strict.

Of course, a state may have a perfectly legitimate reason to impose stricter regulatory restrictions than others. That’s why the algorithm merely creates a “heat map” to start the process of identifying onerous burdens. By producing the necessary analysis in a matter of seconds, it allows officials to focus on applying human insight and judgment.

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Led by Gov. Greg Abbott, Texas officials — noting my findings that their state is America’s fifth-most-regulated and could see a half-trillion-dollar economic boost with its own deregulation effort — are now taking a similar approach to Virginia’s.

Imagine if the federal government were to implement similar technology. Gone would be the days of regulations from different agencies contradicting each other or outdated rules remaining on the books because humans haven’t had the time to update them.

The Trump administration hasn’t shied away from making big bets and pushing fundamental reforms. With just a $100-million investment, officials in the Office of Management and Budget can now transform the way Washington regulates. They should start by talking to their counterparts in Richmond.

Patrick A. McLaughlin, a research fellow at the Hoover Institution, created the RegData and QuantGov projects, which quantify regulations using data-science tools and have informed reforms in several states.

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Ideas expressed in the piece

  • Virginia’s model demonstrates cost-effective regulatory reform: The state paired strict inventory requirements with AI-powered comparison tools, achieving significant savings ($1.2 billion annually) through executive branch efficiency without increased staffing[1][4].
  • States like Idaho prove zero-based regulation works: By requiring agencies to justify every rule and implement rules like “subtract two to add one,” Idaho became the least-regulated state while maintaining public safety and economic dynamism[1][3].
  • Technology enables scalable federal reforms: Virginia’s AI pilot exemplifies how automation can identify redundant/mismatched regulations, flagging discrepancies in training hours or cross-state comparisons for human review[1][4].
  • Steady progress justifies federal investment: Successful state experiments (Ohio’s SB9 requiring 30% cuts, Louisiana’s licensing reciprocity) show systematic approaches yield economic benefits, supporting the wisdom of allocating $100 million for federal OMB process improvements[2][3].

Different views on the topic

  • Executive orders risk transient reforms without legislative backing: Texas/Virginia successes relied on gubernatorial authority, but result [2] emphasizes that without codifying these measures into law, future administrations could reverse progress[2].
  • Impact measurements remain contested: While Virginia claims $372 million savings, Kentucky’s 30% reduction effort saw only $14.7 million in productivity gains for a $325 billion economy – suggesting regulatory savings may be overstated compared to broader economic factors[5].
  • Implementation challenges persist: Even top performers like Ohio face bureaucratic hurdles, requiring annual agency reporting and public hearings to maintain compliance with aggressive cut targets[3].
  • Sector-specific risks remain unaddressed: Opponents might argue that simplifying occupational licensing (e.g., reducing cosmetologist training hours) could undermine quality standards if not carefully calibrated, though the search results provide no evidence of such outcomes[1][3].

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