Measuring chronic and transient components of poverty: a Bayesian approach
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DOI: 10.1007/s00181-006-0110-5
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References listed on IDEAS
- Sylvia. Richardson & Peter J. Green, 1997. "On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 731-792.
- Ravallion, Martin, 1988. "Expected Poverty under Risk-Induced Welfare Variability," Economic Journal, Royal Economic Society, vol. 98(393), pages 1171-1182, December.
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Cited by:
- Michel Lubrano & Zhou Xun, 2021.
"The Bayesian approach to poverty measurement,"
AMSE Working Papers
2133, Aix-Marseille School of Economics, France.
- Michel Lubrano & Zhou Xun, 2021. "The Bayesian approach to poverty measurement," Working Papers halshs-03234072, HAL.
- Michel Lubrano & Zhou Xun, 2023. "The Bayesian approach to poverty measurement," Post-Print halshs-04135764, HAL.
- Shiva Raj Adhikari, Ph.D., 2016. "Poverty Dynamics in Nepal between 2004 and 2011: An Analysis of Hybrid Dataset," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 28(1), pages 27-40, April.
- Michel Lubrano & Zhou Xun, 2023. "The Bayesian approach to poverty measurement," Post-Print hal-04347292, HAL.
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More about this item
Keywords
Birth–death process; Foster Greer and Thorbecke (FGT) measure; Gibbs sampling; Markov chain Monte Carlo (MCMC); C11; C15; D63;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
Statistics
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