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. Author manuscript; available in PMC: 2022 Aug 18.
Published in final edited form as: Am Econ J Econ Policy. 2022 May;14(2):1–33. doi: 10.1257/pol.20200044

Table 6:

The Effects of Payments on Prescription of Target versus Rival Drugs

Dependent Variable:
Number of Patients Prescribed:
Warfarin Target NOAC
(1) (2)
Payments promoting:
Payment count, by type: Any NOAC Target NOAC
 Own Compensation 0.0159 (0.0536) 0.3772 (0.1160)
 Own Food 0.0104 (0.0030) 0.0577 (0.0037)
 Peer Compensation 0.0050 (0.0041) 0.0194 (0.0061)
 Peer Food 0.0054 (0.0015) −0.0006 (0.0013)
Rival NOACs
 Own Compensation −0.1163 (0.0347)
 Own Food 0.0047 (0.0015)
 Peer Compensation −0.0012 (0.0022)
 Peer Food −0.0018 (0.0005)
Mean dependent variable 1.4864 0.5486
N (Doctor × Drug × Quarter) 1,796,544 5,466,420

Notes: Estimates using equation (2) with the dependent variables being the quarterly number of prescribed patients within different segments of the anticoagulant market: warfarin, (the off-patent and unpromoted incumbent) in column 1, and the target NOAC in column 2. The independent variables capture the counts of different types of payments made to the prescribing physicians (“Own”) or to others with whom the prescribing physicians shared patients (“Peers”). See Section 1 for definitions of Food and Compensation. Different panels show payments associated with any NOAC, the target NOAC, and other rival NOACs, as labeled (see Section 4 for details). Physician-drug, specialty-drug-quarter fixed effects, controls for all other types of payments, and payment-type-specific linear time trends included in all specifications. Standard errors are clustered within doctor.