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Related papers: Investigating inequality: a Langevin approach

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The objective of this study is to characterize inequality in infrastructure quality across urban areas. While a growing of body of literature has recognized the importance of characterizing infrastructure inequality in cities and provided…

Computers and Society · Computer Science 2024-03-25 Bo Li , Ali Mostafavi

A number of methods have been introduced in order to measure the inequality in various situations such as income and expenditure. In order to curry out statistical inference, one often needs to estimate the available measures of inequality.…

Methodology · Statistics 2017-12-27 Tchilabalo Abozou Kpanzou , Tertius de Wet , Gane Samb Lo

Decomposition analysis is a critical tool for understanding the social and spatial dimensions of segregation and diversity. In this paper, I highlight the conceptual, mathematical, and empirical distinctions between segregation and…

Methodology · Statistics 2024-02-22 Elizabeth Roberto

This paper introduces the Relative Inequality Index at the Maximum (IDRM), a novel and intuitive measure designed to capture inequality within a population, such as income inequality. The index is based on the idea that individuals…

The quantile ratio index introduced by Prendergast and Staudte 2017 is a simple and effective measure of relative inequality for income data that is resistant to outliers. It measures the average relative distance of a randomly chosen…

Methodology · Statistics 2018-01-01 Luke A. Prendergast , Robert G. Staudte

The empirical literature on the relationship between income inequality and economic growth has produced highly heterogeneous and often conflicting results. This paper investigates the sources of this heterogeneity using a meta-analytic…

Econometrics · Economics 2026-02-23 Lisa Capretti , Lorenzo Tonni

Social inequalities are ubiquitous and evolve towards a universal limit. Herein, we extensively review the values of inequality measures, namely the Gini ($g$) index and the Kolkata ($k$) index, two standard measures of inequality used in…

Physics and Society · Physics 2023-05-03 Suchismita Banerjee , Soumyajyoti Biswas , Bikas K. Chakrabarti , Asim Ghosh , Manipushpak Mitra

Inequality (concentration) curves such as Lorenz, Bonferroni, Zenga curves, as well as a new inequality curve -- the $D$ curve, are broadly used to analyse inequalities in wealth and income distribution in certain populations. Quantile…

Statistics Theory · Mathematics 2023-12-13 Sylwester Piątek

Measures of inequality are often limited in their ability to capture multidimensional aspects that arise from the joint distribution of multiple socio-economic variables. In this paper, we develop bivariate extensions of the Zenga…

Other Statistics · Statistics 2026-04-14 Shifna P R , S. M. Sunoj

This paper attempts to find a relationship between agents' risk aversion and inequality of incomes. Specifically, a model is proposed for the evolution in time of surplus/deficit distribution, and the long-time distributions are…

Economics · Quantitative Finance 2016-05-12 Eleonora Perversi , Eugenio Regazzini

Algorithmic systems increasingly function as epistemic infrastructures that govern the conditions of interpretative access and social belief. Yet, mainstream auditing strategies operationalize fairness primarily in predictive terms - error…

Social and Information Networks · Computer Science 2026-04-27 Camilla Quaresmini , Lisa Piccinin , Valentina Breschi

Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock…

General Finance · Quantitative Finance 2017-02-10 M. L. Bertotti , A. K. Chattopadhyay , G. Modanese

Income segregation measures the extent to which households choose to live near other households with similar incomes. Sociologists theorize that income segregation can exacerbate the impacts of income inequality, and have developed indices…

Methodology · Statistics 2021-11-24 Matthew Simpson , Scott H. Holan , Christopher K. Wikle , Jonathan R. Bradley

The Langevin equation is a common tool to model diffusion at a single-particle level. In non-homogeneous environments, such as aqueous two-phase systems or biological condensates with different diffusion coefficients in different phases,…

The Gini index underestimates inequality for heavy-tailed distributions: for example, a Pareto distribution with exponent 1.5 (which has infinite variance) has the same Gini index as any exponential distribution (a mere 0.5). This is…

Methodology · Statistics 2021-10-06 Sabiou Inoua

This paper applies economic concepts from measuring income inequality to an exercise in assessing spatial inequality in cancer service access in regional areas. We propose a mathematical model for accessing chemotherapy among local…

Econometrics · Economics 2022-09-20 Ka C. Chan , Ruth F. G. Williams , Christopher T. Lenard , Terence M. Mills

This preprint is a text for students and teachers on inequalities. Some standard topics are covered on application of calculus to inequality proving. Many examples are considered, stated, solved or partially solved. Some problems are…

History and Overview · Mathematics 2022-09-07 Sergei Sitnik , Elina Shishkina , Lidiya Kovaleva , Olga Chernova

Distributed order fractional Langevin-like equations are introduced and applied to describe anomalous diffusion without unique diffusion or scaling exponent. It is shown that these fractional Langevin equations of distributed order can be…

Statistical Mechanics · Physics 2012-01-16 C. H. Eab , S. C. Lim

Composite indices like the Gender Equality Index (GEI) are widely used to monitor gender disparities and guide evidence-based policy. However, their original design is often limited when applied to subnational contexts. Building on the GEI…

Applications · Statistics 2026-01-21 Lorenzo Panebianco

Two popular classes of methods for approximate inference are Markov chain Monte Carlo (MCMC) and variational inference. MCMC tends to be accurate if run for a long enough time, while variational inference tends to give better approximations…

Machine Learning · Computer Science 2017-06-21 Justin Domke