Forecasting UK inflation bottom up

51 Pages Posted: 6 Apr 2021

See all articles by Andreas Joseph

Andreas Joseph

Bank of England

Eleni Kalamara

affiliation not provided to SSRN

George Kapetanios

King's College, London

Galina Potjagailo

Bank of England

Date Written: March 26, 2021

Abstract

We forecast CPI inflation in the United Kingdom up to one year ahead using a large set of monthly disaggregated CPI item series combined with a wide set of forecasting tools, including dimensionality reduction techniques, shrinkage methods and non-linear machine learning models. We find that exploiting CPI item series over the period 2011–19 yields strong improvements in forecasting UK inflation against an autoregressive benchmark, above and beyond the gains from macroeconomic predictors. Ridge regression and other shrinkage methods perform best across specifications that include item-level data, yielding gains in relative forecast accuracy of up to 70% at the one-year horizon. Our results suggests that the combination of a large and relevant information set combined with efficient penalisation is key for good forecasting performance for this problem. We also provide a model-agnostic approach to address the general problem of model interpretability in high-dimensional settings based on model Shapley values, partial re-aggregation and statistical testing. This allows us to identify CPI divisions that consistently drive aggregate inflation forecasts across models and specifications, as well as to assess model differences going beyond forecast accuracy.

Keywords: Inflation, forecasting, machine learning, state space models, CPI disaggregated data, Shapley values

JEL Classification: C32, C45, C53, C55, E37

Suggested Citation

Joseph, Andreas and Kalamara, Eleni and Kapetanios, George and Potjagailo, Galina, Forecasting UK inflation bottom up (March 26, 2021). Bank of England Working Paper No. 915, Available at SSRN: https://ssrn.com/abstract=3819286 or http://dx.doi.org/10.2139/ssrn.3819286

Andreas Joseph (Contact Author)

Bank of England ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

Eleni Kalamara

affiliation not provided to SSRN

George Kapetanios

King's College, London ( email )

30 Aldwych
London, WC2B 4BG
United Kingdom
+44 20 78484951 (Phone)

Galina Potjagailo

Bank of England ( email )

Threadneedle Street
London, EC2R 8AH
United Kingdom

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
83
Abstract Views
267
rank
362,155
PlumX Metrics