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Autores principales: Paul Makdissi, Walid Marrouch, Myra Yazbeck
Formato: Artículo Open Access
Publicado: Wiley 2024
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Acceso en línea:https://onlinelibrary.wiley.com/doi/10.1111/roiw.12708
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author Paul Makdissi
Walid Marrouch
Myra Yazbeck
author_facet Paul Makdissi
Walid Marrouch
Myra Yazbeck
Paul Makdissi
Walid Marrouch
Myra Yazbeck
collection Wiley Open Access
contents Monitoring Poverty in a Data‐Deprived Environment: The Case of Lebanon Paul Makdissi Walid Marrouch Myra Yazbeck Review of Income and Wealth AbstractThis paper addresses the lack of data and limited statistical capacity in the Middle East and North Africa, particularly amid Lebanon's economic collapse. We apply a novel data augmentation technique to analyze poverty when traditional income data are limited or unavailable. By adapting existing methods, we recover continuous income distributions from interval data and derive dominance conditions for such data, accounting for non‐response. The proposed approach enables robustness checks by estimating the bounds of admissible cumulative distribution functions. Our empirical analysis uses Lebanese data to perform first‐order dominance tests on these bounds, highlighting the importance of the approach. We demonstrate how alternative data sources can be leveraged for essential poverty analysis. 10.1111/roiw.12708 http://creativecommons.org/licenses/by-nc-nd/4.0/
doi_str_mv 10.1111/roiw.12708
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institution Wiley Open Access
license_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
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spellingShingle Monitoring Poverty in a Data‐Deprived Environment: The Case of Lebanon
Paul Makdissi
Walid Marrouch
Myra Yazbeck
Review of Income and Wealth
Monitoring Poverty in a Data‐Deprived Environment: The Case of Lebanon Paul Makdissi Walid Marrouch Myra Yazbeck Review of Income and Wealth AbstractThis paper addresses the lack of data and limited statistical capacity in the Middle East and North Africa, particularly amid Lebanon's economic collapse. We apply a novel data augmentation technique to analyze poverty when traditional income data are limited or unavailable. By adapting existing methods, we recover continuous income distributions from interval data and derive dominance conditions for such data, accounting for non‐response. The proposed approach enables robustness checks by estimating the bounds of admissible cumulative distribution functions. Our empirical analysis uses Lebanese data to perform first‐order dominance tests on these bounds, highlighting the importance of the approach. We demonstrate how alternative data sources can be leveraged for essential poverty analysis. 10.1111/roiw.12708 http://creativecommons.org/licenses/by-nc-nd/4.0/
title Monitoring Poverty in a Data‐Deprived Environment: The Case of Lebanon
topic Review of Income and Wealth
url https://onlinelibrary.wiley.com/doi/10.1111/roiw.12708