published in: Oxford Economic Papers, 2023, 75 (1), 256–280,
Business and politician interaction is pervasive but has mostly been analysed with a binary approach. Yet the network dimensions of such connections are ubiquitous. We use a unique dataset for seven economies that documents politically exposed persons (PEPs) and their links to companies, political parties and other individuals. With this dataset, we can identify networks of connections, including their scale and composition. We find that all country networks are integrated having a Big Island.
They also tend to be marked by small-world properties of high clustering and short path length. Matching our data to firm level information, we examine the association between being connected and firm-level attributes. The originality of our analysis is to identify how location in a network, including extent of ties and centrality, are correlated with firm scale and performance. In a binary approach such network characteristics are omitted and the scale and economic impact of politically connected business may be significantly mis/under-estimated. By comparing results of the binary approach with our network approach, we can also assess the biases that result from ignoring network attributes.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.