Abstract
A major topic in economics is the analysis of a broad class of phenomena associated with interpersonal relationships, a topic that originally grew from theories of “social capital.” While the concept has been instrumental in bringing increased attention to social effects on economic outcomes, it has increasingly been replaced with approaches that consider instead networks and discrete interactions rather than aggregate measures of social capital. This has been an analytical improvement, but a great deal of work remains to bring empirical validity and relevancy to social network analysis. This paper presents two important approaches for achieving this, statistical analysis and agent-based modeling, and discusses their benefits, limitations, and complementary nature. Rather than waiting for either approach to achieve an ambiguous quality of maturity, integrating statistical analysis with simulation models of networks must begin now to push the frontiers of social network analysis forward.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1 See Farr (Citation2004) for a conceptual history that extends further back than the development of the term as an analytically distinct notion.