What determines the income gap between French male and female GPs - the role of medical practices

BMC Primary Care

Table 4 Decomposition of the difference in income between male and female GPs

Explanatory Factor	Male Advantage $\sum_{k = 1}^{n} \bar{X_{k}^{M}} ({\hat{β}}_{k}^{M} - {\hat{β}}_{k}^{Ref})$ 1		Female Disadvantage $\sum_{k = 1}^{n} \bar{X_{k}^{F}} ({\hat{β}}_{k}^{Ref} - {\hat{β}}_{k}^{F})$ 2		Differences of returns to characteristics = (1) + (2)		Endowment term $\sum_{k = 1}^{n} {\hat{β}}_{k}^{Ref} (X_{k}^{M} - X_{k}^{M})$
Experience’	−0.147	*	−0.089		−0.236		0.040	**
Sector 2	−0.005	*	−0.013		−0.017		−0.000
Rural regions	−0.003		−0.011		−0.014		0.011
Number of consultations and visits per year	−0.185	***	−0.185	***	−0.369	***	0.275	***
Salaried activity (%)	−0.008	**	−0.007		−0.015		0.004
Group practice	0.011		0.031		0.041		0.003
Subtotal	−0.337	*******	−0.273	*******	−0.611	*******	0.333	*******
Constant ${\hat{β}}_{0}^{M} - {\hat{β}}_{0}^{F}$	0.731
Total: (log income difference)	0.453

Notes:
‘ We gathered the experience effect (years of experience + years of experience squared).
This decomposition with the reference being the entire GPs population isolated two terms: one for the male advantage relative to the reference and another for the female disadvantage. We summed these two terms and obtained part of the income gap due to differences of the returns to characteristics (for each characteristic)
***, ** and * denote significance at 1, 5 and 10% levels, respectively.

ISSN: 2731-4553