Forecasting annual inflation with seasonal monthly data: using levels versus logs of the underlying price index

This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many cases, the forecasts based on the original variables result in substantially smaller root mean squared errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are typically small. This outcome sheds doubt on the common practice in the academic literature to forecast inflation rates based on differences of logs.

Willingness to pay for imported and seasonal foods: a UK survey

We report results from an investigation into consumer preferences for locally produced foods. Using a choice experiment we estimate willingness to pay for foods of a designated origin together with certification for organic and free of genetically modified (GM)ingredients. Our results indicate that there is a preference for locally produced food that is GM free, organic, and produced in the traditional season.