Forecasting power-transformed time series data

Paul De Bruin and Philip Hans Franses

Journal of Applied Statistics, 1999, vol. 26, issue 7, 807-815

Abstract: When there is an interest in forecasting the growth rates as well as the levels of a single macro-economic time series, a practitioner faces the question of whether a forecasting model should be constructed for growth rates, for levels, or for both. In this paper, we investigate this issue for 10 US (un-)employment series, where we evaluate the forecasts from a non-linear time series model for power-transformed data. Our main finding is that models for growth rates (levels) do not automatically result in the most accurate forecasts of growth rates (levels).

Date: 1999
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DOI: 10.1080/02664769922043

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