Table 3.

Univariate Sobel–Goodman mediation tests on log income at age 29 (2008)

	Independent variable
	Positive affect (1994)			Positive affect (1996)			Life satisfaction (2001)
Mediating variable (data are from 2008)	Coeff.	P value	%	Coeff.	P value	%	Coeff.	P value	%
Job	0.017	0.000	15	0.025	0.000	22	0.019	0.000	18
Supervision	0.006	0.000	5	0.006	0.000	5	0.006	0.000	6
College	0.039	0.000	36	0.043	0.000	38	0.032	0.000	28
Married	0.004	0.000	4	0.004	0.000	4	0.014	0.000	12
Optimism	0.032	0.000	29	0.036	0.000	32	0.029	0.000	25
Self-esteem	0.017	0.000	15	0.018	0.000	16	0.005	0.000	4
Openness	0.004	0.003	4	0.005	0.010	4	−0.000	0.651	0
Conscientiousness	0.003	0.000	3	0.003	0.000	3	0.004	0.000	3
Extraversion	0.006	0.000	5	0.006	0.000	5	0.004	0.000	4
Agreeableness	−0.001	0.181	−1	−0.002	0.126	−2	−0.000	0.672	0
Neuroticism	0.028	0.000	25	0.031	0.000	27	0.028	0.000	25

Presented are the Sobel test coefficient, P value, and the proportion of the total effect that is mediated (%). All variable coefficients are standardized. Variable definitions are in Table S2. To test for mediation we use the Sobel–Goodman method available in the Stata package that follows the logic described in Baron and Kenny (36). A variable is considered a mediator (M) if it caries some part of the effect from an independent variable (X), here positive affect and life satisfaction, onto a dependent variable (Y), in our case later earnings. Mediation occurs if (i) X significantly predicts M; (ii) X significantly predicts Y in the absence of M; (iii) M significantly predicts Y controlling for X; and (iv) the effect of X on Y shrinks upon addition of M.