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On a Simple Graphical Approach to Modelling Economic Fluctuations with an Application to United Kingdom Price Inflation, 1265 to 2005

Published online by Cambridge University Press:  10 May 2011

W. S. Chan
Affiliation:
Department of Finance, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong., Tel: +852-2609-7715, Fax: +852-2603-6586, Email: chanws@cuhk.edu.hk
M. W. Ng
Affiliation:
Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong., Tel: +852-2859-2466, Fax: +852-2858-9041, Email: h9500301@hkusua.hku.hk
H. Tong
Affiliation:
Department of Statistics, Columbia House, London School of Economics, Houghton Street, London WC2A 2AE, U.K., Tel: +44 (0)2079-556879, Fax: +44 (0)2079-557416, Email: h.tong@lse.ac.uk

Abstract

Structural instability in economic time series is widely reported in the literature. It is most prevalent in such series as price indices and inflation related data. Many methods have been developed for analysing and modelling structural changes in a univariate time series model. However, most of them assume that the data are generated by one fixed type (linear or non-linear) of the time series processes. This paper proposes a strategy for modelling different segments of an economic time series by different linear or non-linear models. A graphical procedure is suggested for detecting the model change points. The proposed procedure is illustrated by modelling annual United Kingdom price inflation series over the period 1265 to 2005. Stochastic modelling of inflation rates is an important topic to actuaries for dealing with long-term index linked insurance business. The proposed method suggests dividing the U.K. inflation series into four segments for modelling. Inflation projections based on the latest segment of the data are obtained through simulations. To get a better understanding of the impact of structural changes on inflation projections we also perform a forecasting study.

Type
Papers
Copyright
Copyright © Institute and Faculty of Actuaries 2006

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