TY - JOUR
T1 - Global poverty: A first estimation of its uncertainty
AU - Moatsos, Michail
AU - Lazopoulos, Achillefs
N1 - Funding Information:
☆ The authors wish to thank the editor and three anonymous reviewers of this journal for their comments and suggestions, Angus Deaton for providing us his estimates on PPP uncertainty, and Robert Allen for providing us his international poverty line preliminary calculations. We also benefited greatly from discussions with Francois Bourguignon, Martin Ravallion, Francisco Ferreira, Christoph Lakner, Prem Sangraula, Robert Inklaar, Daniel Oberski, Mark Sanders, Bram van Besouw, Tim van der Valk, Vincent Schippers, Svetlana Gerakaki, Sarah Carmichael, Auke Rijpma, and Jan Luiten van Zanden. We wish to thank for their remarks participants at the 2017 PEGNet Conference, 2018 PSE Summer School on Development, the 2018 University of Athens Open Seminar in Economic History, and the Utrecht School of Economics 2018 seminar series. We further wish to thank Jaap Oudesluijs for giving us access to necessary hardware, and Kees van Eijden for granting us access to the Dutch HPC (SURFSARA). All analysis has been conducted with R open source statistical computing software ( R Core Team, 2018). All remaining errors are ours alone.
Publisher Copyright:
© 2021 The Author(s)
PY - 2021/6
Y1 - 2021/6
N2 - The dollar-a-day method, applied in monitoring the UN's development goals against poverty, provides no confidence interval for the official figures of global poverty reduction, a practice that does not allow statistical testing. Using Monte Carlo micro-simulations we construct confidence intervals that reflect the error introduced by the process of determining the International Poverty Line, as well as the uncertainty of the involved Purchasing Power Parity exchange rates. These estimates identify a reduction of 5.19% between 1990 and 2015 at 95% confidence level, in stark contrast with the remarkable 73% reduction of global poverty reported in the World Bank official statistics published on September 18, 2018. At the same time, MDG1 obtains with a 80% confidence level. The cost-of-basic-needs method paints a more promising picture identifying a 35.71% reduction at 95% confidence level, while the confidence level at which poverty in 2015 was half of 1990 stands at 46%. We conclude that the derivation method of the international poverty line introduces high levels of uncertainty in the estimates.
AB - The dollar-a-day method, applied in monitoring the UN's development goals against poverty, provides no confidence interval for the official figures of global poverty reduction, a practice that does not allow statistical testing. Using Monte Carlo micro-simulations we construct confidence intervals that reflect the error introduced by the process of determining the International Poverty Line, as well as the uncertainty of the involved Purchasing Power Parity exchange rates. These estimates identify a reduction of 5.19% between 1990 and 2015 at 95% confidence level, in stark contrast with the remarkable 73% reduction of global poverty reported in the World Bank official statistics published on September 18, 2018. At the same time, MDG1 obtains with a 80% confidence level. The cost-of-basic-needs method paints a more promising picture identifying a 35.71% reduction at 95% confidence level, while the confidence level at which poverty in 2015 was half of 1990 stands at 46%. We conclude that the derivation method of the international poverty line introduces high levels of uncertainty in the estimates.
KW - Cost of basic needs
KW - Global Poverty
KW - Mdg1
KW - Confidence interval
KW - Dollar a day
KW - Total error
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=researchintelligenceproject&SrcAuth=WosAPI&KeyUT=WOS:000693689300008&DestLinkType=FullRecord&DestApp=WOS
U2 - 10.1016/j.wdp.2021.100315
DO - 10.1016/j.wdp.2021.100315
M3 - Article
SN - 2452-2929
VL - 22
JO - World Development Perspectives
JF - World Development Perspectives
M1 - 100315
ER -