Understanding poverty merely as a fixed income threshold—whether it be $1.90 or $3.20 per day—grossly oversimplifies the economic reality confronting millions of households. Over the past decade, development economics literature has demonstrated that poverty is not simply a resource deficit, but a dynamic state shaped by the complex interplay of income, expenditures, systemic risks, and behavioral strategies.
Of particular interest is the hypothesis of an S-shaped trajectory out of poverty. According to this model (Carter & Barrett, 2006; Banerjee et al., 2015), the majority of asset-poor households exhibit a low marginal return on effort: they work, yet they cannot accumulate capital. Sustainable transition toward escalating well-being becomes possible only upon reaching a specific threshold of resources or income—the so-called inflection point.
This hypothesis is far from purely theoretical. Several country-level experiments have provided empirical validation, most notably the BRAC program in Bangladesh. Ultra-poor families were provided with assets valued at approximately $500 USD (PPP-adjusted)—typically livestock or equipment—complemented by short-term training. After several years, most participants demonstrated asset growth, income stability, and reduced dependence on aid. This evidence allowed researchers to characterize the program not merely as a successful intervention, but as a structural disruption of the poverty trap mechanism.
Nevertheless, the central question remains open: Is there a universal formula for this inflection point? Furthermore, how can it be accurately measured across diverse countries with varying price levels, employment structures, and social infrastructures?
In this regard, our team addresses three pivotal objectives:
Verify the existence of S-shaped dynamics within the local context. Does the practice confirm a precise point at which the economic behavior of a poor household shifts—moving from mere survival to active asset accumulation? If so, where does this boundary lie in terms of income, savings, and risk indicators?
Develop a calculative approach to determine the exit threshold. We hypothesize that the structural composition of this threshold is largely universal, comprising baseline nutrition, housing, production tools, and elementary healthcare access. However, the cost of these components varies significantly. Our goal is to design an assessment algorithm that accounts for localized prices, seasonality, and typical income structures, essentially establishing the “cost of escaping poverty.”
Map the social watershed from ultra-poverty to transitional states. In practice, poverty is not a binary condition. We aim to construct a qualitative typology across distinct strata:
Ultra-poverty: Resources are insufficient to secure basic caloric intake.
Chronic poverty: Baseline needs are met, but systemic resilience is absent.
Transitional zone: Borderline cases where a household fluctuates on the precipice, highly vulnerable to the slightest external shocks.
Beyond economic behavior, we examine the psychology of poverty—specifically how decision-making and risk perception change relative to resource scarcity. Behavioral economics has established that low-income individuals frequently prioritize short-term gains not due to an inherent “inability to plan,” but because their volatile environment renders long-term planning fundamentally irrational.