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The Old Boy Network: Gender Differences in the Impact of Social Networks on Remuneration in Top Executive Jobs

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  • Lalanne, Marie
  • Seabright, Paul

Abstract

Using an original dataset describing the career history of some 16,000 senior executives and members of the non-executive board of US, UK, French and German companies, we investigate gender differences in the use of social networks and their impact on earnings. There is a large gender wage gap: women (who make up 8.8% of our sample) earned average salaries of $168,000 in 2008, only 70% of the average $241,000 earned by men. This is not due to differences in age, experience or education levels. Women are more likely than men to be non-executives, whose salaries are lower; nevertheless, a substantial gender gap still exists among executives. We construct measures of the number of currently influential people each individual has encountered previously in his or her career. We find that executive men's salaries are an increasing function of the number of such individuals they have encountered in the past while women's are not. Controlling for this discrepancy, there is no longer a significant gender gap among executives. These findings are robust to the use of different years, to the use of salaried versus non-salaried remuneration, and to the use of panel estimation to control rigorously for unobserved individual heterogeneity. In contrast to executives, the salaries of non-executive board members do not display a significant gender wage gap, nor any gender difference in the effectiveness with which men and women leverage their links into salaries. This suggests that adoption of gender quotas for board membership, as has been enacted or proposed recently in several European countries, is unlikely to reduce the gender gap in earnings so long as such quotas do not distinguish between executive and non-executive board members.

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Paper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 689.

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Date of creation: Oct 2011
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Handle: RePEc:ide:wpaper:25165

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  1. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  2. Berardi, Nicoletta & Seabright, Paul, 2011. "Professional Network and Career Coevolution," TSE Working Papers 11-258, Toulouse School of Economics (TSE).
  3. Renneboog, Luc & Zhao, Yang, 2011. "Us knows us in the UK: On director networks and CEO compensation," Journal of Corporate Finance, Elsevier, vol. 17(4), pages 1132-1157, September.
  4. Richard Blundell & Steve Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
  5. Renneboog, L.D.R. & Zhao, Y., 2011. "Us Knows Us in the UK: On Director Networks and CEO Compensation," Discussion Paper 2011-014, Tilburg University, Tilburg Law and Economic Center.
  6. Hwang, Byoung-Hyoun & Kim, Seoyoung, 2009. "It pays to have friends," Journal of Financial Economics, Elsevier, vol. 93(1), pages 138-158, July.
  7. Stefania Albanesi & Claudia Olivetti, 2006. "Gender and Dynamic Agency: Theory and Evidence on the Compensation of Female Top Executives," Boston University - Department of Economics - Working Papers Series WP2006-061, Boston University - Department of Economics.
  8. Renneboog, L.D.R. & Zhao, Y., 2011. "Us Knows Us in the UK: On Director Networks and CEO Compensation," Discussion Paper 2011-014, Tilburg University, Center for Economic Research.
  9. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
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