Forecasting Changes of Economic Inequality: A Boosting Approach
Rangan Gupta (),
Hossein Hassani () and
Emmanuel Silva ()
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Hossein Hassani: Research Institute for Energy Management and Planning, University of Tehran, Tehran, Iran
Emmanuel Silva: Fashion Business School, London College of Fashion, University of the Arts London, 272 High Holborn, London, WC1V 7EY
No 201868, Working Papers from University of Pretoria, Department of Economics
We use a boosting algorithm to forecast changes in three income- and three consumption-based inequality measures. We study quarterly UK data covering the period from 1975Q1 to 2016Q1. We find that the boosted forecasting models, at forecasting horizons of up to one year, have predictive value for changes in the six different inequality measures. Evidence of predictability is strong when we use information criteria that result in relatively parsimonious forecasting models. In addition to lagged inequality measures, stock-market developments and fiscal deficits and, for the consumption-based inequality measures at a forecast horizon of four quarters, economic policy uncertainty and output growth turn out to be relatively important predictors.
Keywords: Inequality; Predictability; Boosting; UK data (search for similar items in EconPapers)
JEL-codes: C53 D63 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cmp and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:pre:wpaper:201868
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