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
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