A general Bayesian approach to meet different inferential goals in poverty research for small areas
Partha Lahiri () and
Jiraphan Suntornchost ()
Additional contact information
Partha Lahiri: Department of Mathematics & Joint Program in Survey Methodology, University of Maryland, College Park, USA
Jiraphan Suntornchost: Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Thailand
Statistics in Transition New Series, 2020, vol. 21, issue 4, 237-253
Abstract:
Poverty mapping that displays spatial distribution of various poverty indices is most useful to policymakers and researchers when they are...
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.exeley.com/exeley/journals/statistics_ ... attrans-2020-040.pdf (application/pdf)
https://www.exeley.com/statistics_in_transition/doi/10.21307/stattrans-2020-040 (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:exl:29stat:v:21:y:2020:i:4:p:237-253
DOI: 10.21307/stattrans-2020-040
Access Statistics for this article
More articles in Statistics in Transition New Series from Polish Statistical Association
Bibliographic data for series maintained by MPS Ltd. ().