A social engineering model for poverty alleviation

Amit Chattopadhyay*, T Krishna Kumar, Iain Rice

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number6345
JournalNature Communications
Volume11
DOIs
Publication statusPublished - 11 Dec 2020

Bibliographical note

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