| FG {ciccr} | R Documentation |
FG
Description
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.
Usage
FG
Format
A data frame with 78,165 rows and 5 variables:
- male
indicator: physician is male
- isMD
indicator: physician has a MD degree
- experYear
experience in years
- flag
indicator: physician billed for more than 100 hours per week
- smallPractice
indicator: number of group practice members less than 6
Source
Fang, H. and Gong, Q. (2020) Data and Code for: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Reply. Nashville, TN: American Economic Association [publisher]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-11-23. doi:10.3886/E119192V1
References
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.