Regensburg 2019 – wissenschaftliches Programm

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SOE: Fachverband Physik sozio-ökonomischer Systeme

SOE 9: Economic Models

SOE 9.2: Vortrag

Dienstag, 2. April 2019, 10:00–10:30, H17

Poverty Dynamics — •Amit Chattopadhyay¹, Iain Rice², and T Krishna Kumar³ — ¹Aston University, Mathematics, Birmingham, B4 7ET, UK — ²Arden University, Coventry, CV3 3RD, UK — ³Rockville-Analytics, Rockville, MD 20850, USA

Economic inequality has been conventionally measured against a unique poverty line; those below this line are deemed poor and those above it, not so! Economists are well aware of the pitfall of such a strict line of demarcation, all based on an exogenous number that may be misleading as well. Departing from such a subjective inequality measure, here we have modeled the largest available dataset (India) using advanced machine learning architecture, over all three expenditure modes (basic food, other food and non-food) that are mutually connected, to avail information on multivariate income distribution functions (PDFs). Independent agent-based stochastic models of trade were then used to validate these PDFs, where trade in assets was only allowed between agents with incomes exceeding a self-consistent mean income over the dynamically evolving trade market, thereby substituting an exogenous poverty line with a data-objectified economic threshold. Together with recent publications (EPL 91, 58003; PRE95, 023109), we have established an alternative probabilistic measure of inequality that is free of personal bias.