Georgia Tech Postdoctoral Fellow Publishes Research on the Effects of Paid Sick Leave on Worker Absenteeism

Postdoctoral Fellow, Jie Chen

Posted September 23, 2020

Postdoctoral Fellow Dr. Jie Chen and coauthors C. D. Meyerhoefer and L. Peng use data from the 2000-2013 Medical Expenditure Panel Survey (MEPS) to study the effects of the introduction of paid sick leave (PSL) on absenteeism and medical care utilization. In the US over 30% of all private-sector workers, mostly amongst low-wage and part-time employees, do not have PSL benefit. As states and localities mandate the introduction of PSL it is important to understand the effects of the introduction of PSL.

Earlier literature is inconclusive. Some find that PSL mandates do not have an effect on employment and wages, and others find that absenteeism is increased with the mandates while others find the reverse. Chen and her colleagues contribute to the debate with a thorough econometric study of the MEPS data from 2000-2013. Using a number of creative applications of the difference-in-difference approach, the authors successfully isolate the relationship between the introduction of PLS and level of absenteeism and healthcare utilization and identify a causal link between them.

They find that the rate of absenteeism and sickness absence days increase for female employees when PSL is introduced, and decrease when it is removed. The authors preferred estimate shows that introduction of PSL leads to a 22-percentage point increase (51%) in absenteeism and 1.7 additional sickness absence days (59%) per year. However, the results for male absenteeism do not indicate a significant increase due to the introduction of PSL. Also, the authors do not find that there is a significant causal relation between the introduction of PSL and healthcare utilization.

Chen is a Postdoctoral Fellow for the Health Economics & Analytics Lab (HEAL). The lab is a unit of the School of Economics that focuses on applying big data analytics and machine learning to large-scale medical claims databases.

Related Link

Contact For More Information

Dr. Jie Chen