Nowcasting the distribution of disposable income: A microsimulation framework enhanced by machine learning

Oecd

No 41, OECD Papers on Well-being and Inequalities from OECD Publishing

Abstract: Timely and accurate distributional income data are essential for monitoring inequality, assessing the adequacy of tax-benefit systems, and designing policy responses during periods of rapid economic change. However, income and inequality statistics derived from EU-SILC are typically published with a lag of 12 to 18 months, limiting their usefulness during fast-moving shocks such as the COVID-19 pandemic, the 2022 energy price shock, or a severe recession. This paper presents results from a new nowcasting framework designed to reduce this information gap for EU Member States. By combining machine-learning (ML) forecasts of market income with EUROMOD microsimulation under the latest available tax-benefit rules, the framework produces timely estimates and forecasts of income inequality.

Keywords: inequality; machine learning; microsimulation; nowcasting; poverty rate (search for similar items in EconPapers)
JEL-codes: C53 D31 (search for similar items in EconPapers)
Date: 2026-10-13
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Persistent link: https://EconPapers.repec.org/RePEc:oec:wiseaa:41-en

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