With a new deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the `global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reductio…
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48 results for “poverty reduction”
Subsidized insurance reduces poverty by providing social benefits and lowering government costs.
problem Reducing poverty through effective social protection mechanisms.
method Modeling household capital dynamics under four insurance frameworks (uninsured, insured, insured with subsidies, insured with flexible premiums) to assess poverty reduction and governmental costs.
result Subsidized insurance schemes provide maximum social benefits while reducing governmental costs, effectively reducing poverty.
Modeling poverty transitions in India over 54 years, showing rising but persistent poverty.
problem Understanding and addressing poverty dynamics in India over long periods.
method Stochastic model of Geometric Brownian Motion with reallocation (RGBM).
result Annual poverty transitions are common, but poverty persists, especially among the poorest.
Mapping the spatial distribution of poverty in developing countries remains an important and costly challenge. These "poverty maps" are key inputs for poverty targeting, public goods provision, political accountability, and impact evaluation, that are all the more important given the geographic dispersion of the remain…
Wariness and Poverty Trapsq-fin.CP
Wariness affects poverty traps and equilibrium diversity in economic models.
problem The impact of wariness on poverty traps and equilibrium diversity in economic models.
method An overlapping generations model to explore the effects of wariness on poverty traps and equilibrium diversity.
result Wariness can amplify or mitigate the likelihood of poverty traps and can lead to multiple intertemporal equilibria.
We provide investment advice for an individual who wishes to minimize her lifetime poverty, with a penalty for bankruptcy or ruin. We measure poverty via a non-negative, non-increasing function of (running) wealth. Thus, the lower wealth falls and the longer wealth stays low, the greater the penalty. This paper general…
Spatial machine learning improves poverty targeting in Indonesia.
problem Conventional PMT methods have high exclusion and inclusion errors due to spatial dependencies and regional heterogeneity.
method Integrates spatial contiguity matrices into SML models to identify and compare poverty clusters.
result SML reduces exclusion errors from 28% to 20% compared to standard machine learning models.
Fuel poverty affects between 50 and 125 million households in Europe and is a significant issue for both developed and developing countries globally. This means that fuel poor residents are unable to adequately warm their home and run the necessary energy services needed for lighting, cooking, hot water, and electrical…
Study analyzes household capital risk and poverty trapping, deriving a new function for capital deficit distribution.
problem Analyzing the risk of household capital falling into poverty.
method Introduced a new Gerber-Shiu function to model trapping time and capital deficit distribution.
result Derived a model for capital deficit distribution at trapping using GB distributions.
In a recent work (Chattopadhyay, A. K. et al, Europhys. Lett. {\bf 91}, 58003, 2010) based on food consumption statistics, we showed how a stochastic agent based model could represent the time variation of the income distribution statistics in a developing economy, thereby defining an alternative \enquote{poverty index…
Growth, Poverty Trap and Escapephysics.soc-ph
Model shows how capital accumulation can lead to poverty traps and well-being states.
problem Capital accumulation and its effects on poverty and well-being.
method Stochastic Solow growth model with sigmoidal saving fraction and bimodal steady state distribution.
result Existence of poverty trap with fluctuation-driven transitions between poverty and well-being states.
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Povertycs.LG
With the rapid expansion of mobile phone networks in developing countries, large-scale graph machine learning has gained sudden relevance in the study of global poverty. Recent applications range from humanitarian response and poverty estimation to urban planning and epidemic containment. Yet the vast majority of compu…
Scoping review of EO-ML methods for causal inference in poverty geography.
problem Lack of thorough documentation and best practices for EO-ML methods in causal analysis.
method Comprehensive scoping review cataloging five principal approaches.
result Detailed protocol for integrating EO data into causal analysis.
When considering answering important questions with data, unsupervised data offers extensive insight opportunity and unique challenges. This study considers student survey data with a specific goal of clustering students into like groups with underlying concept of identifying different poverty levels. Fuzzy logic is co…
Study optimizes CT and microinsurance for efficient social protection in low-income countries.
problem Efficient targeting of cash transfers to reduce social protection costs in low-income countries.
method Modelled household capital dynamics using piecewise-deterministic Markov process, derived HJB equation for optimal injection, used dynamic programming.
result Optimal level of capital injection above poverty threshold for cost-effective social protection.
Study examines how insurance affects households prone to proportional losses, especially those near poverty.
problem Impact of insurance on households susceptible to proportional losses, focusing on poverty traps.
method Modelled proportional capital losses with insurance, derived closed formulae and non-local differential equations.
result New formulae and methods to calculate trapping probability, constraints on parameters to prevent certainty of trapping.
Classic economic science is reaching the limits of its explanatory powers. Complexity science uses an increasingly larger set of different methods to analyze physical, biological, cultural, social, and economic factors, providing a broader understanding of the socio-economic dynamics involved in the development of nati…
A control-theoretic model tackles microfinance sustainability issues.
problem High default rates in microfinance due to lack of data and information.
method A novel control-theoretic model that learns microfinance decision policies.
result The model achieves financial inclusion, fairness, social welfare, and sustainability.
Inequalities of wealth distribution in a conservative economycond-mat.stat-mech
We analyze a conservative market model for the competition among economic agents in a close society. A minimum dynamics ensures that the poorest agent has a chance to improve its economic welfare. After a transient, the system self-organizes into a critical state where the wealth distribution have a minimum threshold, …
We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the…
A new CA-GAN architecture improves minority class data generation in health datasets.
problem Algorithmic bias due to health data poverty and underrepresentation of minority groups.
method Proposes CA-GAN architecture to address shortcomings of resampling and GAN-based approaches.
result CA-GAN outperforms SMOTE and WGAN-GP* in generating authentic minority class data and maintaining original distribution.
Impacts of Regional Trade Agreements(RTAs) on Food Security: A Case of ASEAN Free Trade Agreementq-fin.GN
Discriminatory trade liberalization policies are becoming more popular among world economies. Countries are motivated to enter for regional trade agreements to capture faster economic growth for alleviating poverty. In developing economies like most of the member countries of the Association of South East Asian Nations…
Satellite imagery helps adjust for unobserved confounders in observational studies.
problem Adjusting for confounding factors in observational studies with non-tabular data like satellite imagery.
method Formalizing conditions for causal effect identification, estimation, and sensitivity analysis.
result Demonstrated the use of satellite imagery as a proxy for unobserved confounders in anti-poverty aid programs.
Drivers, Receivers, and Dynamic Linkages: The Directed Structure of SDG Interdependence, 2000--2024stat.AP
Study maps interdependence of SDGs, finds complex, dynamic linkages.
problem Identify which SDGs promote progress and how quickly.
method Used a balanced panel of 114 countries from 2000 to 2024, applying two estimators to recover directed interaction network and measure dynamic linkages.
result 84 goal linkages survive false-discovery control, showing both synergies and trade-offs, with no single goal acting as a universal accelerator.
Paper analyzes factors affecting COVID-19 risk in US counties.
problem Identifying factors influencing COVID-19 risk in US counties.
method Combines unsupervised (K-means clustering) and supervised learning models.
result Mean temperature, poverty, obesity, and other factors are most significant.
Poor economies not only produce less; they typically produce things that involve fewer inputs and fewer intermediate steps. Yet the supply chains of poor countries face more frequent disruptions---delivery failures, faulty parts, delays, power outages, theft, government failures---that systematically thwart the product…
New proof shows local wealth condensation in economic models with biases.
problem Economic models with biases leading to wealth condensation.
method Elementary proof based on properties of wealth distributions.
result Local wealth condensation observed in models with wealth or poverty advantages.
We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative household surveys. It employs standard statistical learning techniques---cross-validation and parameter regularization---which together reduce the extent to which the model is over-…
Thermodynamic description of world GDP distribution over countriescond-mat.stat-mech
The world GDP distribution is described using thermodynamics principles.
problem Understanding the distribution of GDP among countries.
method Applied Rayleigh-Jeans thermalization to GDP data.
result Emergence of low GDP states similar to condensation in optics.
Many models of market dynamics make use of the idea of conservative wealth exchanges among economic agents. A few years ago an exchange model using extremal dynamics was developed and a very interesting result was obtained: a self-generated minimum wealth or poverty line. On the other hand, the wealth distribution exhi…
Paper introduces multi-scale methods to improve CATE estimation from EO data.
problem Challenges in balancing fine-grained and contextual information in EO-based causal inference.
method Multi-Scale Representation Concatenation, combining Vision Transformer and Causal Forests.
result Multi-scale approach captures effect heterogeneity better than single-scale models.
We consider a multi-armed bandit problem with covariates. Given a realization of the covariate vector, instead of targeting the treatment with highest conditional expectation, the decision maker targets the treatment which maximizes a general functional of the conditional potential outcome distribution, e.g., a conditi…
Reduces variance in noisy social outcomes to improve policy evaluation and optimization.
problem Improving access to opportunity through personalized treatment decisions.
method Data-driven dimensionality-reduction using reduced rank regression to denoise multiple outcomes.
result Improves estimation error in policy evaluation and optimization, including on real-world data.
This paper combines ideas from classical economics and modern finance with the general Lotka-Volterra models of Levy & Solomon to provide straightforward explanations of wealth and income distributions. Using a simple and realistic economic formulation, the distributions of both wealth and income are fully explained. B…
Obtaining detailed and reliable data about local economic livelihoods in developing countries is expensive, and data are consequently scarce. Previous work has shown that it is possible to measure local-level economic livelihoods using high-resolution satellite imagery. However, such imagery is relatively expensive to …
In this paper, a frequency coefficient based on the Sen-Shorrocks-Thon (SST) poverty index notion is proposed. The clustering SST index can be used as the method for determination of the connection between similar neighbor sub-clusters. Consequently, connections can reveal existence of natural homogeneous. Through esti…
We study heterogeneity in the effect of a mindset intervention on student-level performance through an observational dataset from the National Study of Learning Mindsets (NSLM). Our analysis uses machine learning (ML) to address the following associated problems: assessing treatment group overlap and covariate balance,…
New methods reduce bias in machine learning predictions for causal inference without extra data.
problem Machine learning predictions from satellite data shrink toward the mean, leading to biased causal estimates.
method Two post-hoc correction methods: Linear Calibration Correction (LCC) and Tweedie's approach, reduce shrinkage-induced bias.
result Tweedie's method yields nearly unbiased treatment-effect estimates, enabling multiple trials with a single map.
We develop a new statistical test for comparing variables with varying scales.
problem Comparing variables with different scales in multidimensional spaces.
method Order based on expectations of random variables, generalized stochastic dominance (GSD) order, regularized statistical test, linear optimization, imprecise probability models.
result Validated through multidimensional data from various fields.
Data mining revealed a cluster of economic, psychological, social and cultural indicators that in combination predicted corruption and wealth of European nations. This prosperity syndrome of self-reliant citizens, efficient division of labor, a sophisticated scientific community, and respect for the law, was clearly di…
This paper introduces a novel framework for designing fair and sustainable unemployment benefits, grounded in cooperative game theory and real-time fiscal policy. The labor market is modeled as a coalitional game, where a random subset of participants is employed, generating stochastic economic output. To ensure fairne…
The prominent inequality of wealth and income is a huge concern especially in the United States. The likelihood of diminishing poverty is one valid reason to reduce the world's surging level of economic inequality. The principle of universal moral equality ensures sustainable development and improve the economic stabil…
Public debt is one of the important economic variables that quantitatively describes a nation's economy. Because bankruptcy is a risk faced even by institutions as large as governments (e.g. Iceland), national debt should be strictly controlled with respect to national wealth. Also, the problem of eliminating extreme p…
Model trains agents to optimize saving and investment strategies for diverse retirement needs.
problem Optimal saving and investment strategies for individuals in varied employment and income profiles.
method Deep reinforcement learning to train intelligent agents with heterogeneous profiles.
result Flexible methodology estimates lifetime consumption and investment choices for different profiles.
Enhancing Efficiency of Pension Schemes through Effective Risk Governance: A Kenyan Perspectiveq-fin.RM
Study finds risk management significantly improves pension scheme efficiency in Kenya.
problem Improving efficiency of pension schemes in Kenya.
method Panel data analysis of 128 pension schemes from 2015-2021.
result Risk management significantly mediates the relationship between corporate governance and pension scheme efficiency.
The paper addresses treatment recommendation problems by optimizing distributional characteristics.
problem Optimizing treatment recommendations based on distributional targets.
method Characterizes the problem's difficulty and proposes near-optimal policies.
result Characterizes the difficulty of the problem and proposes near-regret optimal policies.
Artificial intelligence (AI) has evolved considerably in the last few years. While applications of AI is now becoming more common in fields like retail and marketing, application of AI in solving problems related to developing countries is still an emerging topic. Specially, AI applications in resource-poor settings re…
Study examines financial performance determinants of Kenyan microfinance banks.
problem Competition from commercial banks threatens microfinance banks' financial performance.
method Descriptive research design with secondary data analysis.
result Operational efficiency, capital adequacy, and firm size positively correlate with financial performance.