John Fallon

Competitive Occupational Licensure: Doctors Versus Chiropractors

This paper provides the first analysis of competitive occupational licensure, where substitute professions maintain separate licensing boards that set entry requirements strategically. I develop and structurally estimate a model where professional organizations choose licensing stringency to maximize industry profits while accounting for competitive responses, as workers with heterogeneous abilities select occupations based on expected returns and consumers observe only average quality within each profession. Testing this theory using historical competition between medical doctors (MDs) and chiropractors (DCs) from 1907–1960, I exploit digitized American Medical Association records and state-by-year variation in chiropractic board adoption. Medical boards responded strategically by increasing college requirements by 10 percentage points, mandating internships (10+ percentage points), and reducing pass rates by 5 percentage points. Structural estimation reveals that observed equilibria closely approximate profit-maximizing sequential competition rather than welfare-maximizing behavior.

Fewer Licenses, Similar Teachers: Changing Licensing Tests in Indiana

with Marcus A. Winters, PhD

We use longitudinal administrative data from Indiana to examine changes in teacher quality following the state's shift to a more stringent licensure test. Despite a significant drop in new licenses issued following the change, the overall quality of incoming teachers and the relative quality of licensed teachers compared to unlicensed teachers remained largely unchanged. We find some heterogeneity by subject and school setting, with urban schools experiencing a modest decline in teacher quality, particularly in math.

Extracting Value from Coworkers: Identifying Optimal Pairing Strategies

Workers learn from their peers, but which collaborations build lasting skills and which do not? I study co-teaching, where a general education teacher and a special education teacher share responsibility for the same classroom, using administrative data on all teachers in Indiana from 2012–2019. Comparing teachers before and after co-teaching, I find that pairing with highly experienced partners (16+ years) raises student achievement by 0.10σ after teachers return to solo instruction, while pairing with inexperienced partners produces no gains. Longer collaborations provide no additional benefit, and teachers with 2–3 years of prior experience gain more than novices.

Human Assistance Can't Beat Algorithms in Online Hiring

with Emma Wiles and John Horton

We study a randomized experiment in which a large online labor market assigned human assistants to job posts. Treated employers received 13% more applications and 35% more interviews, but hired at the same rate as controls who had access only to algorithmic tools. Treated employers also spent 10% less on hires in the first 30 days, suggesting human assistance produced worse matches. We develop a model of delegated recruiting with shared information noise to explain these findings.