| FG_CC {ciccr} | R Documentation |
FG_CC
Description
Case-control sample extracted from Fang and Gong (2020). The case-control sample is extracted from Fang and Gong (2020) by the following procedure. The case sample is composed of 2,261 flagged physicians (that is, those who billed for more than 100 hours per week). The control sample of equal size is randomly drawn without replacement from the pool of physicians who were never flagged. The sample is composed of 4,522 physicians who billed at least 20 hours per week.
Usage
FG_CC
Format
A data frame with 4,522 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.