Forecasting a time series of Lorenz curves: One-way functional analysis of variance

Fuente: arXiv
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Auteur principal: Shang, Han Lin
Format: Preprint
Publié: 2025
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author Shang, Han Lin
author_facet Shang, Han Lin
contents The Lorenz curve is a fundamental tool for analysing income and wealth distribution and inequality at national and regional levels. We utilise a one-way functional analysis of variance to decompose a time series of Lorenz curves and develop a method for producing one-step-ahead point and interval forecasts. The one-way functional analysis of variance is easily interpretable by decomposing an array into a functional grand effect, a functional row effect and residual functions. We evaluate and compare the forecast accuracy between the functional analysis of variance and three non-functional methods using the Italian household income and wealth data.
format Preprint
id arxiv_https___arxiv_org_abs_2504_04437
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Forecasting a time series of Lorenz curves: One-way functional analysis of variance
Shang, Han Lin
Methodology
Applications
62R10
The Lorenz curve is a fundamental tool for analysing income and wealth distribution and inequality at national and regional levels. We utilise a one-way functional analysis of variance to decompose a time series of Lorenz curves and develop a method for producing one-step-ahead point and interval forecasts. The one-way functional analysis of variance is easily interpretable by decomposing an array into a functional grand effect, a functional row effect and residual functions. We evaluate and compare the forecast accuracy between the functional analysis of variance and three non-functional methods using the Italian household income and wealth data.
title Forecasting a time series of Lorenz curves: One-way functional analysis of variance
topic Methodology
Applications
62R10
url https://arxiv.org/abs/2504.04437