I | II | III | IV | V | VI | |
---|---|---|---|---|---|---|
Whole sample | Low testosterone | Whole sample | ||||
Testosterone (pg/mL) | 0.002^{***} | 0.001 | 0.006^{*} | 0.003^{*} | ||
(0.001) | (0.001) | (0.003) | (0.002) | |||
Average digit ratio | −4.262^{***} | −4.730^{***} | ||||
(1.342) | (1.420) | |||||
Baron-Cohen eye test | −0.003 | |||||
(0.007) | ||||||
Gender: Female = 1 | −0.182^{**} | −0.085 | −0.276^{***} | −0.223^{***} | −0.128 | |
(0.072) | (0.107) | (0.085) | (0.055) | (0.123) | ||
Observations | 379 | 379 | 165 | 152 | 392 | 146 |
Pseudo R-squared | 0.023 | 0.035 | 0.049 | 0.115 | 0.03 | 0.139 |
This table shows maximum likelihood estimates of a probit model where the dependent variable is equal to one if the subject has chosen finance as his/her first job after graduation, and zero otherwise. This variable is regressed on the level of salivary testosterone. The coefficients reported are the marginal effects on the probability that the first employment is a finance job from an infinitesimal change in the testosterone level, and a discrete change in the gender variable (when included). The marginal effect is calculated at the mean values of all regressors. There is a positive correlation between a finance career and salivary testosterone, especially in the sample of subjects with <83.3 pg/mL of testosterone. Heteroschedasticity robust standard errors are reported in brackets.
↵* Means significantly different from zero at the 10% level (two-tail t test),
↵** at the 5% level, and
↵*** at the 1% level.