A social engineering model for poverty alleviation

Amit K. Chattopadhyay (), T. Krishna Kumar and Iain Rice
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Amit K. Chattopadhyay: Aston University, Department of Mathematics
T. Krishna Kumar: Rockville-Analytics
Iain Rice: Birmingham City University

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract Poverty, the quintessential denominator of a developing nation, has been traditionally defined against an arbitrary poverty line; individuals (or countries) below this line are deemed poor and those above it, not so! This has two pitfalls. First, absolute reliance on a single poverty line, based on basic food consumption, and not on total consumption distribution, is only a partial poverty index at best. Second, a single expense descriptor is an exogenous quantity that does not evolve from income-expenditure statistics. Using extensive income-expenditure statistics from India, here we show how a self-consistent endogenous poverty line can be derived from an agent-based stochastic model of market exchange, combining all expenditure modes (basic food, other food and non-food), whose parameters are probabilistically estimated using advanced Machine Learning tools. Our mathematical study establishes a consumption based poverty measure that combines labor, commodity, and asset market outcomes, delivering an excellent tool for economic policy formulation.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-20201-4

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DOI: 10.1038/s41467-020-20201-4

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