Working Paper: CEPR ID: DP16761
Authors: Jos Tavares; Sharmin Sazedj
Abstract: This paper advances the literature on the gender pay gap amongst top managers, byexplicitly assessing the relevance of professional networks. We use data on the universe offirms in Portugal, where female top managers earn 25% less than their male counterparts,conditional on age, education and firm tenure. We estimate that 20% of the above femalemale earnings difference is due to differences in networks across gender. Making useof Gelbach’s decomposition, we find that the network effect can be ascribed to firmsorting, i.e. well-connected managers tend to be associated to higher paying firms. Byfocusing on episodes of transitions between firms, and relying on a propensity scorematching procedure, we estimate that around 90% of the gender pay gap emergesduring the hiring process, and is only slightly aggravated thereafter, due to biased careerprogression. Roughly one third of the gender gap can be attributed to firm sorting, twothirds of which to differences in networks. We then examine the gender compositionof female and male CEOs’ networks. While we find no evidence that females benefitdifferently from network size, we do find evidence that male connections are morevaluable. If, however, we proxy for the inner circle of a manager, taking into accountthe proximity of connections, we conclude that same gender connections gain relevance.These results suggest that connections between females do play an important role in theexisting corporate framework where males are over-represented. We conclude that policiesfurthering female representation in leadership positions can have positive spillover effectfor other women.
Keywords: gender gap; networks; CEO compensation; firm sorting
JEL Codes: G34; J30; J24; L14
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Female top managers in Portugal (J16) | Gender pay gap (J31) |
| Differences in professional networks between genders (J16) | Gender pay gap (J31) |
| Firm sorting (L20) | Gender pay gap (J31) |
| Differences in network composition (D85) | Gender pay gap (J31) |
| Network effect during the hiring process (D85) | Gender pay gap (J31) |
| Biased career progression (J62) | Gender pay gap (J31) |
| Network size (D85) | Value of connections (D85) |
| Male connections (Y80) | Value of connections (D85) |
| Female connections in inner circle (Y80) | Value of connections (D85) |
| Policies promoting female representation (J16) | Positive spillover effects for other women (F63) |