Inflation Forecast: Just use the Disaggregate or Combine it with the Aggregate

Kausik Chaudhuri and Saumitra Bhaduri

Journal of Quantitative Economics, 2019, vol. 17, issue 2, No 5, 343 pages

Abstract: Abstract Using data from India, the paper provides three stylize facts about the inflation forecasting: (a) using disaggregate data helps to achieve gains in forecast accuracy relative to forecasting the aggregate inflation directly; (b) using weights derived from spillover index for component forecasting compared to the official weights or the criterion suggested by Bates and Granger further improves efficiency; (c) combining disaggregates along with aggregate data is beneficial for forecasting inflation. Results also highlights the fact that inclusion of too many disaggregates might result in efficiency loss in short-term forecasting but definitely results in gain for the medium-term.

Keywords: Spillover index; Combination forecast; Disaggregate information; Inflation forecasting; India; C53; E31 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s40953-019-00155-1

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