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Network‐based appointments and board diversity

Datos Bibliográficos

ID9726537
AutoresMarie Lalanne (European Commission, autor de correspondencia)
Año2023
Volumen90
Número358
Páginas409-452
Fecha de publicación2023-04-01
Open AccessSí
TipoARTICLE
RevistaEconomica (JOURNAL)
Identificadores de la revistaISSN: 0013-0427 • E-ISSN: 1468-0335
EditorialWiley (PUBLISHER • GB)
DOI10.1111/ecca.12462
OpenAlexW4320915803
IdiomaEN
Citas recibidas1
Referencias citadas59

This paper investigates the occurrence of network‐based appointments and its impact on board diversity. I use data on independent board appointments between 2006 and 2012 in large publicly listed firms in the USA, and exploit directors' CVs to uncover past social connections between candidates and current directors along various dimensions—from employment, education, army and social activities. I first estimate the probability of obtaining a board seat when being socially connected to members of the recruiting board. Using different assumptions to recreate the unobserved pool of candidates, I find that being socially connected to someone on the board increases the chances of obtaining the board seat between 35.8 and 41.1 percentage points, after controlling for a large set of firm and director characteristics together with firm and director fixed effects. I then study the change in board diversity following these appointments. While appointments of new independent directors affect board diversity positively, those that are made through networks are not significantly different. However, this is likely the result of appointing directors from a significantly homogeneous sample of individuals, whether connected or not, and suggests that in order to increase board diversity, efforts should be directed towards increasing diversity in the pool of candidates

Affect (linguistics) · Business · Computer security · Corporate governance · Diversity (politics) · Exploit · Gender diversity · Homogeneous · On board · Order (exchange) · Political science · Sample (material) · Set (abstract data type) · Accounting · Computer Science · Corporate Finance and Governance · Engineering · Finance · Gender Diversity and Inequality · Law · Mathematics · Political Influence and Corporate Strategies · Psychology

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Citas por año1
Intervalo de citas2025 - 2025 (1)
Altamente citadoNo

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