Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/196788 
Year of Publication: 
2019
Series/Report no.: 
IZA Discussion Papers No. 12290
Publisher: 
Institute of Labor Economics (IZA), Bonn
Abstract: 
Texas is the only state that does not mandate that employers carry workers' compensation insurance (WC) coverage. We employ a quasi-experimental design paired with a novel machine learning approach to examine the effects of switching from traditional workers' compensation to a so-called non-subscription program in Texas. Specifically, we compare before and after effects of switching to non-subscription for employees in Texas to contemporaneously measured before and after differences for non-Texas-based employees. Importantly, we study large self-insured companies operating the same business in multiple states in the US; hence the non-Texas operations represent the control sites for the Texas treatment sites. The resulting difference-in-differences estimation technique allows us to control for any companywide factors that might be confounded with switching to non-subscription. Our empirical approach also controls for injury characteristics, employment characteristics, industry, and individual characteristics such as gender, age, number of dependents, and marital status. Outcomes include number of claims reported, medical expenditures, indemnity payments, time to return to work, likelihood of having permanent disability, likelihood of claim denial, and likelihood of litigation. The data include 25 switcher companies between the years 2004 and 2016, yielding 846,376 injury incidents. Regression findings suggest that indemnity, medical payments, and work-loss fall substantially. Claim denials increase and litigation falls.
Subjects: 
workers' compensation insurance
non-subscription
difference-in-differences
triple differences
machine learning
PDS-LASSO
JEL: 
C54
C55
I13
J32
J38
Document Type: 
Working Paper

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