Department of Economics, University of Venice "Ca' Foscari
Abstract
This paper contributes to the literature on interlocking directorates (ID) by providing a new solution to the two econometric issues arising in the joint analysis of interlocks and firm performance which are the endogenous nature of ID and sample selection bias due to the exclusion of isolated firms. Some key determinants of ID network formation are identified and used to check for endogeneity. We analyze the impact of the positioning in the network on firms’ performance and inspect how the impact varies across firms of different sizes drawing on information relating to 37,324 firms in the interlocking network which, to our knowledge, is the widest dataset ever used in approaching the study of ID. Our results, made robust for endogeneity and sample selection bias, suggest that eigenvector centrality and the clustering coefficient have a positive and significant impact on all the performance measures and that this effect is more pronounced for small firms
