New Publication in Social Network Analysis and Mining
Philip Leifeld, Professor in Social Statistics at ºÚÁÏÍø³Ô¹Ï±¬ÁÏ, together with Yuanyuan Shang, has published a new study in Social Network Analysis and Mining.
Philip Leifeld, Professor in Social Statistics at ºÚÁÏÍø³Ô¹Ï±¬ÁÏ, together with Yuanyuan Shang, has published a new study in Social Network Analysis and Mining (2026): Applying a Panel Network Formation Model to Limited Partnership Matching in the Private Capital Market.
Abstract
In private capital investment, limited partners (LPs) and general partners (GPs) frequently encounter the challenge of finding suitable counterparts amid limited information, a process often hindered by market inefficiencies. This article addresses this issue by exploring the micro-level mechanisms that shape private capital networks, employing temporal exponential random graph models. Our findings uncover activity and popularity effects, persistence mechanisms, and homophily in preferences concerning region, strategy, and industry. These factors jointly shape the dynamically evolving network structure across asset classes and the hybrid network with all asset classes, revealing a shared network formation process. This article offers practical insights into the matching problem within the private capital market.
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