Sunbelt XXXI International Network for Social Network ... - INSNA

A Social Network Analysis Of Tsimane’ Market IntegrationSchultz, Alan F.; Tallman, Paula S.; Monteban, Madalena; Bond, Megan; Goldstein, Ruth; Bernstein, AlissaOverlapping Personal NetworksWhole Networks, Personal Networks, Egonet, OverlappingSAT.AM1The Tsimane’ of lowland Bolivia live relatively egalitarian lives but are beginning to face increasing integration into markets and the corollary threat of growinginequalities. These inequalities may be reflected in the social structure of Tsimane’ communities. This project used a social network approach to understandthe variable distribution of market integration within and between communities. There were two phases to this process. First, three respondents within acommunity were asked to evaluate the ties between all unique pairs of community members. I examine the extent to which these assessments agreed andcombined them into one whole network. In the whole network those that were on the periphery of the network were individuals with higher marketintegration. For a second study, I conducted 29 Egonet interviews across two villages, half the respondents provided 25 alters and half 8 alters. I combinedthese personal networks into one whole network using the overlap of names and personal attributes. My analysis will show how these overlapping personalnetworks reflect the whole network structure of the communities and common alters on the periphery and between the villages.A Social Network Perspective On The Quantity Theory Of Money: A First ExplorationDekker, DavidNetworks and EconomicsEconomic NetworksFRI.PM2Social network theory has much to offer in bridging the micro‐macro gap in economics. This paper explores some ideas about possibilities to link macroeconomicvariables to social network structures. Specifically, attention is focused on the implications of degree distributions in trade networks on the velocityof money variable in the monetarist Quantity Theory of Money. Velocity is defined as distance over time, and velocity of money is the average frequency amonetary unit is used in a given time unit. In network terms the “average frequency a monetary unit is used” (v) translates into the walks with average lengthv. In this paper it is argued that it matters for economies through what structures walks are traversed. A walk of length v that includes 2 nodes has differenteconomic implications than those that include v+1 nodes. Furthermore, walks of money often are dependent on the trade network structure, i.e. v‐step linksand 1‐step links are dependent and a function of degree distributions. In economic terms this implies that micro individual relational behavior (1‐step linking)has a direct effect on the (macro) quality of the velocity of money.