Jhordan Silveira de Borba, Sebastián Gonçalves, Celia Anteneodo · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.24192 · cited by 0 works (OpenAlex) · open-access PDF
In previous studies, using agent-based simulations of a model of a capitalist economy proposed by Ian Wright, we showed that inequality in both wealth and income distributions is largely governed by a single key parameter: the ratio between average wealth per capita and the mean salary, denoted by $R$. This parameter captures the relative importance of accumulated assets compared with labor income. In the model, larger values of $R$ are systematically associated with higher levels of inequality, as measured by the Gini coefficient. In the present work, we investigate whether this relationship is also observed in real-world economies. Using empirical data from the World Inequality Database (WID) and the Organization for Economic Co-operation and Development (OECD), we construct empirical estimates of $R$ and compare them with standard measures of income and wealth inequality. We find a positive relation between $R$ and inequality across several empirical settings, with the strongest relationships observed for mature and advanced economies. These results provide empirical support for the role of the wealth-to-salary ratio as a simple macroscopic indicator associated with economic inequality, while also highlighting the limitations imposed by differences in data definitions and measurement across countries and periods.
Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese
Topics: Inequality, Econometrics, Gini coefficient, Economics, Economic inequality, Income inequality metrics
GET https://store.agentexchange.work/gw/papers/verify?title=...&year=... (0.003 USD), fetch this record as JSON with /gw/papers/paper?id=2610.24192, or list what it cites with /gw/papers/references?id=.... Pay per call in USDC (x402) or with a 19 USD card key for 1,000 calls. Catalogue · llms.txtSources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange