2025 Licensing Database Compares State Regulations

In late December, the Knee Regulatory Research Center released their Annual Licensing Database Snapshot: 2025; the database offers a resource for professionals, policymakers and researchers interested in the scale, scope and requirements of occupational licenses across the United States. According to Conor Norris of the Knee Regulatory Research Center, the 2025 data includes 96 professions across all 50 states and the District of Columbia. “For state agencies,” Norris explains, “this data can be useful to compare licensing requirements in their state with those in other states. The dataset includes a number of professions that are not licensed in every state. Even when a profession is universally licensed, the requirements for licensure can vary considerably between states. Regulators can use these comparisons to identify where their licensing requirements stand out. For example, agencies can see whether their requirements are comparatively more demanding, more restrictive in how applicants qualify, or out of step with prevailing approaches in other states. By making these differences visible, the dataset provides a foundation for evidence-based discussions about whether licensing rules are appropriately calibrated to protect consumers while supporting a robust workforce.”

Norris also says the data helps to assess the effects of changes in licensing requirements over time. The KRRC database currently includes three years of data for the initial 50 professions included in the 2023 database release. And each year, the database adds new professions. “Research using these data,” he says “can help agencies assess whether reforms are achieving their intended goals and support future policy changes with empirical evidence. As debates over workforce mobility and access to services continue, the database offers a timely resource for understanding how licensing rules differ across states.”

The team at the Knee Regulatory Research Center’s database reviews state statutes, administrative codes, and licensing board websites, explains Norris, to identify the licensing requirements for an occupational license.

Conor Noris works as an Assistant Professor of General Business at the John Chambers College of Business and Economics at West Virginia University and the Director of Labor for the Knee Regulatory Research Center.

Download the database on the Knee Regulatory Research Center website.

Amid Fraud Claims, HHS Announces More Changes to Child Care Funding

The U.S. Department of Health and Human Services announced on January 5 a plan to rescind a series of Biden-era regulations related to federal funding sources for child care. The action comes less than a week after HHS confirmed the suspension of all federal funding through the same program. The move follows allegations of fraud by Minnesota Child Care providers. According to NPR, Biden administration rules urged states to pay child care providers based on enrollment rather than verified attendance, pay in advance of services and prioritize guaranteed slots with providers over vouchers. Child care advocates interviewed by NPR said states already use many controls to prevent fraud and that these changes introduce “chaos and confusion.” In a separate NPR report on January 6, child care advocates called the current state of child care funding “stable and affordable.”

Citizens Prefer In-Person State Services: NASCIO Report

The January 7 NASCIO Voices podcast from the National Association of State Chief Information Officers breaks down key findings from their AI research. Harnessing GenAI to Elevate the Citizen Experience reveals that citizens prefer in-person services over AI options; according to the stats, 63% of citizens prefer in-person services over AI “even if it means longer wait times.” The data comes from a survey of 1,000 U.S. residents who regularly interact with government services. The podcast focused on the broader topic of how citizens and CIOs view the challenges of accessing state services – where they do and do not align.

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