A Snapshot of Occupational Licensing Regulation in the Midwest and Mid-Atlantic States

Occupational licensing laws mandate that aspiring workers complete minimum levels of education and training, pass exams, and meet a variety of other requirements before they can begin working in their chosen field of employment. Occupational licensing affects more than 20 percent of the workforce. Its prevalence has steadily increased since the 1950s, when just 5 percent of the workforce required a license in order to work in a profession. The expressed purpose of occupational licensing laws is to ensure that professionals are competent and to protect the safety of customers. Research suggests that licensing may also support the development of human capital during a professional’s career.

However, licensing has been shown to have drawbacks. By restricting potential new entrants into a field, licensing protects professionals from competition and raises prices for consumers. Because licensing laws are passed at the state level, licensing also reduces interstate mobility. Meanwhile, the evidence that it improves quality is mixed at best.

In this policy brief, we compare the overall stringency of occupational licensing regulations for select states in the Midwest and mid-Atlantic states. This direct comparison allows us to identify states within a region whose level of occupational licensing regulation makes them outliers and states that should serve as a model for reform.

In our comparison group we find that Indiana was the most stringently regulated state, having the most restrictions and total words pertaining to occupational licensing of the states in our sample. Ohio was a close second with respect to occupational licensing restrictions and word count. Pennsylvania and Maryland were the least restrictive states in our group, with far fewer restrictions and total words than Indiana and Ohio. At the industry level, states also vary considerably in how much licensing burdens the same industry. Some states have relatively few restrictions for an industry, while others heavily regulate that same industry. These large differences in regulations for the same industry should motivate policymakers to reconsider the merits of stringent occupational licensing regulations.

Data Source

Our primary data source is Occupational Licensing (OL) RegData, a derivative of the RegData series from the Mercatus Center at George Mason University. Introduced in 2012, RegData uses machine learning and text analysis to identify restrictions contained in a jurisdiction’s regulations. Restrictions are instances of the words and phrases “shall,” “must,” “may not,” “required,” and “prohibited” within a regulation. OL RegData’s algorithm works by predicting the probability that a regulation contains language pertaining to occupational licensing. In addition, the algorithm identifies regulated occupations using a similar approach.

Additionally, we map each state’s regulations to the occupation categories using the Standard Occupational Classification (SOC) system. The classification of occupational licensing regulations into the SOC system allows for comparisons across states, including a comparison of the level of restrictions within an occupation.

Typical methods of gathering licensing regulations, which do not employ machine learning, have several shortcomings. It is time consuming to have an individual or team of individuals read through every state code to find the relevant information. Methods that rely solely on human effort suffer from possible error and subjectivity. Finally, it is extremely difficult and time consuming for humans to gather information with the level of detail of RegData.

The traditional approach for gathering licensing data is often to focus on one or a small number of occupations and a limited subset of variables. Two organizations, the Knee Center for the Study of Occupational Regulation and the Institute for Justice, have been able to generate datasets that cover a large number of occupations, but they simultaneously face limitations in the variables they can gather because of their labor-intense approaches. The size of the administrative code of each state makes the collection process difficult for traditional legislative research. This limitation creates an opportunity for software-based approaches, like that of RegData, to gather a substantial amount of information.

Strengths of Our Approach

Our method allows us to compare the overall levels of occupational licensing across states, unlike other methods that compare specific variables such as application fees or education requirements. Our data include measures of the stringency of regulations, including the length of the relevant portion of the code, the number of restrictions, and the difficulty of reading the text. We use these measures to compare the overall stance of states’ occupational regulatory environments. By comparing these measures across states, we can identify outlier states that need reform and model states with less burdensome regulatory environments.

RegData allows us to examine the data by occupation using the three-, four-, and five-digit codes in the standard SOC system. This approach allows us to compare across occupations within and between states. Similar occupations that pose a similar level of risk for customers yet have substantially different regulatory stances in the same state provide some evidence that the regulations are being driven by professional organizations’ rent-seeking rather than by a desire to protect public safety. Another advantage of classifying occupations according to the SOC system is that researchers will be able to directly use data that are collected by agencies such as the Census Bureau and the Bureau of Labor Statistics to examine the effects of occupational licensing on wages, employment, and other labor market outcomes.

Results

Comparisons at the State Level

Table 1. Occupational Licensing Restrictions and Words

Source: Kofi Ampaabeng et al., “State Occupational Licensing RegData” (dataset), QuantGov, Mercatus Center at George Mason University, 2019, https://www.quantgov.org/; Dick M. Carpenter II et al., License to Work: A National Study of Burdens from Occupational Licensing, 2nd ed. (Arlington, VA: Institute for Justice, 2017).

OL RegData has occupational licensing restriction data for 37 states. These states are included in the State RegData data series, which is also based on the RegData project. For this brief, we select four contiguous Midwest and mid-Atlantic states. Table 1 ranks the states in the sample by number of occupational licensing regulatory restrictions. The number of restrictions gives a measure of the burden professionals must bear to meet a state’s occupational licensing requirements. The number of words in the licensing code is an alternate measure of a state’s stance toward occupational licensing; a greater number of words implies that states are licensing more occupations, placing more requirements on each licensed occupation, or a combination of the two. Combined, occupational licensing restrictions and occupational licensing words provide evidence of the regulatory burden imposed by state licensing laws.

We find a considerable variation between states in terms of OL restrictions, which ranged from a high of 26,152 in Indiana to a low of 5,851 in Pennsylvania. Similarly, Indiana had the most OL words in the region. Ohio was second, with two-thirds the number of OL words as Indiana. Pennsylvania and Maryland have the fewest words.

As a comparison with existing data on occupational licensing, we also include the Institute for Justice licensing burden ranking for each state in our sample. A higher rank (e.g., 50) corresponds with a lower burden. The Institute for Justice measures the barriers to entering low-income occupations using the cost in terms of time and money of licensure requirements. States with higher fees, more days of required education, and more exams have a higher rank.

The results of this comparison suggest that Indiana has the most onerous licensing requirements in this region. Having the most restrictions and number of words, Indiana’s regulations are the most numerous and difficult to satisfy, although Ohio is similar. Compared to the nearby states of Pennsylvania and Maryland, the two least restrictive states, Indiana is substantially more restrictive. The differences between our ranking and the Institute for Justice’s ranking may be driven by the differences in methodologies. RegData measures the number of restrictions, not the burden of each restriction. Additionally, we include all occupations in our study, not only low-income occupations.

Table 2. Average Sentence Length 

Source: Ampaabeng et al., “State Occupational Licensing RegData” (dataset).

Average sentence length (see table 2) is a measure of the average number of words per sentence. A longer average sentence suggests that a state has more complex regulations or regulations that are more difficult to understand.

Ohio has the longest average sentence length, with 34 words per sentence. Maryland and Indiana have similar average sentence lengths of 28 and 24 words, respectively. Pennsylvania has the shortest average sentence length, making its occupational licensing regulations the most straightforward and easy to read and understand.

Individual State Results

Table 3. Indiana Occupational Licensing Restrictions by Occupation

Note: SOC = Standard Occupational Classification.

Source: Ampaabeng et al., “State Occupational Licensing RegData” (dataset).

Indiana has the highest number of regulated occupations, with 48 of the 50 being regulated (see table 3). The most heavily regulated occupation is health diagnosing and treating practitioners. Healthcare workers have the most words and restrictions, and also the longest average sentence length, of any occupation regulated in the state. Counselors, social workers, and other community and social service specialists are the next most heavily regulated occupation, followed closely by architects, surveyors, and cartographers. The occupation with the fourth-most occupational licensing restrictions, private detectives and investigators, has the second-greatest average sentence length.

Table 4. Maryland Occupational Licensing Restrictions by Occupation

Note: SOC = Standard Occupational Classification.

Source: Ampaabeng et al., “State Occupational Licensing RegData” (dataset).

Maryland regulates 16 of the 50 occupation codes on our list (see table 4). Health diagnosing and treating practitioners are the most heavily regulated occupation in Maryland, with roughly half of the restrictions and total words of all the occupations. Their average sentence length is also 382 words, more than 300 words longer than for the average occupation. Heating, air conditioning, and refrigeration mechanics and installers and counselors, social workers, and other community and social service specialists are the next most heavily regulated occupations.

Table 5. Ohio Occupational Licensing Restrictions by Occupation

Note: SOC = Standard Occupational Classification.

Source: Ampaabeng et al., “State Occupational Licensing RegData” (dataset).

In Ohio, 11 of the 50 occupations are regulated (see table 5). Health diagnosing and treating practitioners are the most heavily regulated occupation, with nearly half the total restrictions and total words. Their average sentence length is 609, almost five times the average sentence length for all occupations. Private detectives and investigators are the second most heavily regulated occupation. Counselors, social workers, and other community and social service specialists and barbers, hairdressers, hairstylists, and cosmetologists are also heavily regulated.

Table 6. Pennsylvania Occupational Licensing Restrictions by Occupation

Note: SOC = Standard Occupational Classification.

Source: Ampaabeng et al., “State Occupational Licensing RegData” (dataset).

In Pennsylvania, 20 of the 50 occupations are regulated (see table 6). Health diagnosing and treating practitioners is the most heavily regulated occupation, with nearly half of the total restrictions and words for all the occupations in the state, and their average sentence length is nearly double that of the next-highest occupation. Counselors, social workers, and other community and social service specialists is the second most heavily regulated occupation. Dental hygienists are the next most heavily regulated occupation.

Cross-Occupation Comparison

Breaking our results down by SOC code allows us to compare results across occupations and states. The occupations that consistently face the greatest number of restrictions across states are health diagnosing and treating practitioners and counselors, social workers, and other community and social service specialists. The most heavily restricted occupation is health diagnosing and treating practitioners. Their average number of restrictions is 6,180, with an average of 463,085 separate licensing restrictions. Counselors, social workers, and other community and social service specialists have an average of 1,865 restrictions in our sample and an average of 156,925 words.

For many occupations in our sample, the regulatory stance differs considerably across the four states. For instance, Indiana places more than 2,400 restrictions on architects, while Ohio places fewer than 900, and Maryland and Pennsylvania place fewer than 150. Dental hygienists are regulated inconsistently between states. The number of restrictions on dental hygienists ranges from 1,052 in Ohio to 254 in Indiana. Even for occupations that are regulated more consistently between states, we observe outlier states. Ohio is unusually restrictive for health diagnosing and treating practitioners and private detectives, while the other states have consistent regulatory stances. Ohio also strictly regulates psychologists, while Indiana, Maryland, and Pennsylvania place fewer restrictions on professionals in that industry. Maryland places many more restrictions on morticians than comparison states.

Several occupations are licensed and heavily regulated in some states but unlicensed in other states. Heating, air conditioning, and refrigeration mechanics and installers are licensed and regulated in Maryland and Pennsylvania, but not in Ohio and Indiana. Supervisors of farming, fishing, and forestry workers are subject to licensing in Indiana and Pennsylvania, but not in Maryland and Ohio.

Healthcare professionals face very stringent regulations, and this is perhaps unsurprising, given the risk to the health and safety of patients posed by receiving substandard care. However, by designing such complex and disparate regulatory systems, states make it difficult for professionals to move between states. This creates rigidity in the healthcare system and limits the system’s ability to respond to shocks in demand. Outside healthcare, it is worth pondering the health and safety rationale for Maryland placing 513 restrictions on morticians—more than eight times the number of restrictions the state places on aircraft pilots and flight engineers. Discrepancies like these highlight the need for a careful reconsideration of occupational licensing restrictions.

Conclusion

In this policy brief, we use a novel dataset generated using OL RegData to explore differences in the stringency of occupational licensing for select states in the Midwest and mid-Atlantic region. Indiana has more occupational licensing restrictions and words than any other state in our comparison group, and Ohio is a close second. Pennsylvania has the fewest occupational licensing restrictions and words and the shortest average sentence length. Perhaps not surprisingly, occupational licensing restrictions are most prevalent in healthcare. More granular comparisons of occupational licensing across states suggest that there are significant differences in the burden of state regulation. It is not immediately clear why regulations should differ to this degree for professions that do not greatly differ across states. With this additional information in hand, policymakers should carefully reconsider occupational licensing laws and make sure that those laws are not overly burdensome and are providing the right mix of consumer protection and flexibility.