Forecasting Distribution of Inflation Rates: Functional Autoregressive Approach

Forthcoming in Journal of the Royal Statistical Society: Series A.

45 Pages Posted: 20 Feb 2010 Last revised: 26 Feb 2015

See all articles by Kausik Chaudhuri

Kausik Chaudhuri

Indira Gandhi Institute of Development Research (IGIDR)

Minjoo Kim

University of Liverpool - Accounting and Finance Division

Yongcheol Shin

Independent

Date Written: November 30, 2014

Abstract

In line with the recent developments on the statistical analysis of functional data, we develop the semiparametric functional autoregressive (FAR) modeling approach to the density forecasting analysis of national inflation rates using sectoral inflation rates in the UK over the period January 1997-September 2013. The pseudo out-of-sample forecasting evaluation and test results provide an overall support to superior performance of our proposed models over the aggregate autoregressive models and their statistical validity. The fan-chart analysis and the probability event forecasting exercise provide a further support for our approach in a qualitative sense, revealing that the modified FAR models can provide a complementary tool for generating the density forecast of inflation, and analyse the performance of the central bank in achieving announced inflation target. As inflation targeting monetary policies are usually set with recourse to the medium-term forecasts, our proposed work may provide policymakers with an invaluably enriched information set.

Keywords: Time-varying Cross-sectional Distribution, Functional Autoregression, Nonparametric Bootstrap, Density and Probability Forecasting of the UK Inflation

JEL Classification: C14, C53, E31

Suggested Citation

Chaudhuri, Kausik and Kim, Minjoo and Shin, Yongcheol, Forecasting Distribution of Inflation Rates: Functional Autoregressive Approach (November 30, 2014). Forthcoming in Journal of the Royal Statistical Society: Series A.. Available at SSRN: https://ssrn.com/abstract=1555257 or http://dx.doi.org/10.2139/ssrn.1555257

Kausik Chaudhuri

Indira Gandhi Institute of Development Research (IGIDR) ( email )

Gen A.K. Vaidya Marg Santoshnagar
Goregaon (East)
Bombay 400065, Maharashtra
India
91-022-840-0019 (Phone)

Minjoo Kim (Contact Author)

University of Liverpool - Accounting and Finance Division ( email )

227 Grove
Management School
Liverpool, Liverpool L69 3BX
United Kingdom

HOME PAGE: http://https://www.liverpool.ac.uk/management/staff/minjoo-kim/

Yongcheol Shin

Independent

No Address Available

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