A Network Structure of ROSCAs (Rotating Savings and Credit Associations) : ERGMs (Exponential Random Graph Models) Applied to a Leaders' Network in Rural Uzbekistan
This 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.
|Date of creation:||Feb 2010|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: +81 (0)11-706-3163
Fax: +81 (0)11-706-4947
Web page: http://www.econ.hokudai.ac.jp/en08/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:hok:dpaper:221. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Hokkaido University Library)
If references are entirely missing, you can add them using this form.