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Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 2924-2940 |
| Number of pages | 17 |
| Journal | Journal of Applied Statistics |
| Volume | 52 |
| Issue number | 15 |
| Early online date | 8 Apr 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Bibliographical note
© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.Keywords
- Functional principal component analysis
- Gini index
- functional time series
- high dimensionality
- income and wealth inequality
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Dive into the research topics of 'Forecasting a time series of Lorenz curves: one-way functional analysis of variance'. Together they form a unique fingerprint.Projects
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FT24: Functional Panel Data Analysis: Harnessing Big Data for Society
Shang, H. (Primary Chief Investigator)
1/01/25 → 31/12/28
Project: Research