Measuring chronic and transient components of poverty: a Bayesian approach


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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/48680

Title:	Measuring chronic and transient components of poverty: a Bayesian approach
Authors:	Hasegawa, Hikaru¹ Browse this author →KAKEN DB
Authors:	Ueda, Kazuhiro² Browse this author
Authors(alt):	長谷川, 光¹
Authors(alt):	上田, 和宏²
Keywords:	Birth–death process
	Foster Greer and Thorbecke (FGT) measure
	Gibbs sampling
	Markov chain Monte Carlo (MCMC)
Issue Date:	Nov-2007
Publisher:	Physica Verlag, An Imprint of Springer-Verlag
Journal Title:	Empirical Economics
Volume:	33
Issue:	3
Start Page:	469
End Page:	490
Publisher DOI:	10.1007/s00181-006-0110-5
Abstract:	After the publication of Ravallion’s (1988) seminal work on chronic and transient poverty, wide attention has been given to the components of poverty. We propose a Bayesian mixture model to measure poverty and divide it into chronic and the transient poverty using the Foster, Greer and Thorbecke (FGT) measure. These two types of poverty are illustrated using the Panel Study of Income Dynamics (PSID) data.
Rights:	The original publication is available at www.springerlink.com
Type:	article (author version)
URI:	http://hdl.handle.net/2115/48680
Appears in Collections:	経済学院・経済学研究院 (Graduate School of Economics and Business / Faculty of Economics and Business) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 長谷川光

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