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Panel A (health-based channel) and panel B (indirect effect through the mother) of table 9 show these results. The results in panel A show that GP gender match does not have an impact on the health-related outcomes of the child. The one exception is fertility, which displays a statistically significant effect. However, the point estimate is not economically meaningful. The results in panel B show that assignment to a same-gender GP does not affect the mother's education, labor market, and health outcomes. Taken together, the results in table 9 suggest that the effects we identify in section IV are unlikely to operate through a health-based, nonrole model channel or an indirect role model channel via the mother's interaction with the GP.

Table 9.

Potential Pathways and Mechanisms

A: Potential indirect effects through health
	Number of GP visits	Still with assigned GP	Number of diagnoses	Mental health diagnosis	Birth control visits	Fertility
Same-Gender GP	−0.009	−0.014	−0.039	−0.000	0.002	−0.000^**
	(0.070)	(0.019)	(0.028)	(0.000)	(0.005)	(0.000)
Mean	1.166	0.613	2.241	0.078	0.069	0.000
B: Potential indirect effects through mother
	Years of	Total	Not in	Number of	Mental health	Birth control
	education	income	labor force	diagnoses	diagnosis	visits	Fertility
Same-Gender GP	0.004	−0.004	0.009	0.176	−0.003	0.001	−0.001
	(0.109)	(0.021)	(0.012)	(0.141)	(0.018)	(0.012)	(0.001)
Mean	14.146	12.740	0.066	3.614	0.186	0.068	0.003

A: Potential indirect effects through health
	Number of GP visits	Still with assigned GP	Number of diagnoses	Mental health diagnosis	Birth control visits	Fertility
Same-Gender GP	−0.009	−0.014	−0.039	−0.000	0.002	−0.000^**
	(0.070)	(0.019)	(0.028)	(0.000)	(0.005)	(0.000)
Mean	1.166	0.613	2.241	0.078	0.069	0.000
B: Potential indirect effects through mother
	Years of	Total	Not in	Number of	Mental health	Birth control
	education	income	labor force	diagnoses	diagnosis	visits	Fertility
Same-Gender GP	0.004	−0.004	0.009	0.176	−0.003	0.001	−0.001
	(0.109)	(0.021)	(0.012)	(0.141)	(0.018)	(0.012)	(0.001)
Mean	14.146	12.740	0.066	3.614	0.186	0.068	0.003

The table shows the $β_{1}$ coefficients obtained through estimation of equation (1) as described in the text: $y_{i} = α + β_{1} G P_M a t c h_{i} + τ_{t} + π_{m} + θ_{c} + ρ_{d} + ε_{i}$ ⁠. $y_{i}$ denotes the outcome, and each estimation includes municipality (⁠ $π_{m}$ ⁠), year of swap (⁠ $τ_{t}$ ⁠), birth year (⁠ $θ_{c}$ ⁠), and previous GP (⁠ $ρ_{d}$ ⁠) fixed effects. Standard errors are clustered at the GP. The sample in panel A includes all girls born between 1988 and 1996 who were subject to an exogenous GP swap prior to age 15. The sample in panel B includes all mothers to girls who were born between 1988 and 1996 and exposed to an exogenous GP swap prior to age 15. Outcomes are measured when the girls are 15 years old. Income is reported in log form. Significant at $^{*}$ 10%, $^{* *}$ 5%, $^{* * *}$ 1%.

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Figure 2.

Authors' estimation of a modified version of equation (1) as described in the text and reproduced here for clarity: yi=α+β1GP_Matchi+τt+πm+θc+ρd+εi. yi is a general term denoting the outcome listed on the horizontal axis, and each estimation includes municipality (πm), year of swap (τt), birth year (θc), and previous GP (ρd) fixed effects. Standard errors are clustered at the level of the exogenously assigned GP. The sample includes all girls born between 1988 and 1996 who were subject to at least one exogenous GP swap prior to age 15. The specification that replaces the previous GP fixed effects with previous GP characteristics includes GP age, gender, and Norwegian-born status. For each of the four outcomes, the following specification legend applies: Specification 1: no fixed effects; specification 2: cohort-by-municipality fixed effects; specification 3: cohort fixed effects and municipality-specific trends; specification 4: cohort, municipality, and year fixed effects; specification 5: cohort, municipality, and year fixed effects, and controls for previous GP characteristics; specification 6: cohort and previous GP fixed effects; specification 7: cohort, municipality, and previous GP fixed effects; specification 8: cohort, year, and previous GP fixed effects; specification 9: cohort, municipality, year, and previous GP fixed effects.

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Estimated Effects with Varying Fixed Effects

Authors' estimation of a modified version of equation (1) as described in the text and reproduced here for clarity: $y_{i} = α + β_{1} G P_M a t c h_{i} + τ_{t} + π_{m} + θ_{c} + ρ_{d} + ε_{i}$ ⁠. $y_{i}$ is a general term denoting the outcome listed on the horizontal axis, and each estimation includes municipality (⁠ $π_{m}$ ⁠), year of swap (⁠ $τ_{t}$ ⁠), birth year (⁠ $θ_{c}$ ⁠), and previous GP (⁠ $ρ_{d}$ ⁠) fixed effects. Standard errors are clustered at the level of the exogenously assigned GP. The sample includes all girls born between 1988 and 1996 who were subject to at least one exogenous GP swap prior to age 15. The specification that replaces the previous GP fixed effects with previous GP characteristics includes GP age, gender, and Norwegian-born status. For each of the four outcomes, the following specification legend applies: Specification 1: no fixed effects; specification 2: cohort-by-municipality fixed effects; specification 3: cohort fixed effects and municipality-specific trends; specification 4: cohort, municipality, and year fixed effects; specification 5: cohort, municipality, and year fixed effects, and controls for previous GP characteristics; specification 6: cohort and previous GP fixed effects; specification 7: cohort, municipality, and previous GP fixed effects; specification 8: cohort, year, and previous GP fixed effects; specification 9: cohort, municipality, year, and previous GP fixed effects.

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