1998
DOI: 10.1017/s1357321700000155
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The Wilkie Model for Retail Price Inflation Revisited

Abstract: A first order autoregressive model was proposed in Wilkie (1995) for the retail price inflation series as a part of his stochastic investment model. In this paper we apply time-series outlier analysis to the data set and a revised model is derived. It significantly alleviates the problem of leptokurtic and positive skewed residual distribution as found in the original model. Finally, ARCH models for the original series and the outlier-adjusted data are also considered.

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Cited by 9 publications
(7 citation statements)
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“…Table 4.3 shows the details of the detected outliers and the corresponding events. Chan & Wang (1998) and Hendry (2001) identify similar turbulent points for the U.K. inflation series.…”
Section: Resultsmentioning
confidence: 76%
“…Table 4.3 shows the details of the detected outliers and the corresponding events. Chan & Wang (1998) and Hendry (2001) identify similar turbulent points for the U.K. inflation series.…”
Section: Resultsmentioning
confidence: 76%
“…Stochastic Investment Modelling: a Multiple Time-Series Approach 547 2.5 Chan & Wang (1998) performed a time-series outlier analysis on U.K. inflation data. In some circumstances, not adjusting for outliers could lead to model mis-specification (Chan, 1992) and biased parameter estimation (Chang et al, 1988).…”
Section: á Preliminary Data Analysismentioning
confidence: 99%
“…Wright (1998) proposed an alternative model based on vector autoregression. Chan & Wang (1998) refined the price inflation component of the Wilkie model by performing a time-series outlier analysis. Whitten & Thomas (1999) suggested a threshold-type non-linear model for U.K. investment series.…”
mentioning
confidence: 99%
“…A stochastic investment model tries to project how investment returns on different assets such as equities or bonds vary over time. It is possible to use this to work out how investing in different assets could affect investments over time [7].…”
Section: Introductionmentioning
confidence: 99%