Interlocking Directorate and Firm Performance: Distance, Size, and Endogeneity

Background: This paper contributes to the literature on interlocking directorates (ID) by providing a new solution to the two inference 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. Method: Some key determinants of ID network formation are identified and used to control for endogeneity. The instruments for eigen-centrality and clustering coefficient are based on the features of the degree-neighbors of a firm. The estimated the Mills ratio is used as a regressor in the second stage of the two-stage least square to deal with the sample selection bias. 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 Results: 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. Conclusion: A new inference framework is provided to assess the impact of the positioning of the firm in the network on its performance while controlling for endogeneity in the network structure. An application of the proposed framework to an original ID dataset provides new empirical results on the firm positing within the ID network.