Dataset from Fang and Gong (2017,2020). The original dataset in Fang and Gong (2017) is updated in Fang and Gong (2020) after Matsumoto (2020) pointed out data and coding errors in the original work. We use the updated version of the dataset. The sample is composed of 78,165 physicians who billed at least 20 hours per week.
FGA data frame with 78,165 rows and 5 variables:
indicator: physician is male
indicator: physician has a MD degree
experience in years
indicator: physician billed for more than 100 hours per week
indicator: number of group practice members less than 6
Fang, H. and Gong, Q. (2017). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked. American Economic Review, 107(2), 562-91.
Matsumoto, B. (2020). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment. American Economic Review, 110(12), 3991-4003.
Fang, H. and Gong, Q. (2020). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Reply. American Economic Review, 110(12): 4004-10.