A Network Structure of ROSCAs (Rotating Savings and Credit Associations) : ERGMs (Exponential Random Graph Models) Applied to a Leaders' Network in Rural Uzbekistan
AbstractThis paper empirically analyzes a network structure created by the ROSCAs (Rotating Savings and Credit Associations) related to a leaders' network in rural Uzbekistan. The estimation methodology is based on the recent development of ERGMs (Exponential Random Graph Models) whose approximate maximum likelihood estimators are produced by MCMC (Markov Chain Monte Carlo) algorithms. The paper reveals the tendencies of the transitive triad structure of the network that can facilitate the tracking of defecting members.
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Bibliographic InfoPaper provided by Graduate School of Economics and Business Administration, Hokkaido University in its series Discussion paper series. A with number 221.
Length: 24 pages
Date of creation: Feb 2010
Date of revision:
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ROSCAs; Networks; Risk-Sharing; ERGMs; MCMC; O1; I3;
Find related papers by JEL classification:
- O1 - Economic Development, Technological Change, and Growth - - Economic Development
- I3 - Health, Education, and Welfare - - Welfare and Poverty
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-04-17 (All new papers)
- NEP-MFD-2010-04-17 (Microfinance)
- NEP-ORE-2010-04-17 (Operations Research)
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