This article investigates the extent to which national brand and private label (store brand) prices behave differently as food price inflation changes. Empirical tests using a range of indices support the hypotheses that rising commodity and fuel prices lead to relatively larger surges in private label prices. When food prices are rising or high, the average price difference between national brands and private labels shrinks. The findings have implications for understanding the welfare effects of private labels. Moreover, they suggest that food price inflation is stronger for low-income households as food prices rise.

In this paper we adopt the multiple time-series modelling approach suggested by Tiao & Box (1981) to construct a stochastic investment model for price inflation, share dividends, share dividend yields and long-term interest rates in the United Kingdom. This method has the advantage of being direct and transparent. The sequential and iterative steps of tentative specification, estimation and diagnostic checking parallel those of the well-known Box-Jenkins method in the univariate time-series analysis. It is not required to specify any a priori causality as compared to some other stochastic asset models in the literature.

In this paper the ‘Wilkie investment model’ is discussed, updated and extended. The original model covered price inflation, share dividends, share dividend yields (and hence share prices) and long-term interest rates, and was based on data for the United Kingdom from 1919 to 1982, taken at annual intervals. The additional aspects now covered include: the extension of the data period to 1994 (with omission of the period from 1919 to 1923); the inclusion of models for a wages (earnings) index, short-term interest rates, property rentals and yields (and hence property prices) and yields on index-linked stock; consideration of data for observations more frequently than yearly, in particular monthly data; extension of the U.K. model to certain other countries; introduction of a model for currency exchange rates; extension of certain aspects of the model to a larger number of other countries; and consideration of more elaborate forms of time-series modelling, in particular cointegrated models and ARCH models.

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.

This paper reviews the stochastic asset model described in Wilkie (1995) and previous work on refining this model. The paper then considers the application on non-linear modelling to investment series, considering both ARCH techniques and threshold modelling. The paper suggests a threshold autoregressive (TAR) system as a useful progression from the Wilkie (1995) model. The authors are making available (on compact disk) a collection of spreadsheets, which they have used to simulate the stochastic asset models which are considered in this paper.

In this paper we review the Wilkie asset model for a variety of UK economic indices, including the Retail Prices Index, both without and with an ARCH model, the wages index, share dividend yields, share dividends and share prices, long term bond yields, short term bond yields and index-linked bond yields, in each case by updating the parameters to June 2009. We discuss how the model has performed from 1994 to 2009 and estimate the values of the parameters and their confidence intervals over various sub-periods to study their stability. Our analysis shows that the residuals of many of the series are much fatter-tailed than in a normal distribution. We observe also that besides the stochastic uncertainty built into the model by the random innovations there is also parameter uncertainty arising from the estimated values of the parameters.