The Role of the Log Transformation in Forecasting Economic Variables

Referierte Aufsätze Web of Science

Helmut Lütkepohl, Fang Xu

In: Empirical Economics 42 (2012), 3, S. 619-638

Abstract

For forecasting and economic analysis many variables are used in logarithms (logs). In time series analysis, this transformation is often considered to stabilize the variance of a series. We investigate under which conditions taking logs is beneficial for forecasting. Forecasts based on the original series are compared to forecasts based on logs. For a range of economic variables, substantial forecasting improvements from taking logs are found if the log transformation actually stabilizes the variance of the underlying series. Using logs can be damaging for the forecast precision if a stable variance is not achieved.



JEL-Classification: C22
Keywords: Autoregressive moving average process, Forecast mean squared error, Instantaneous transformation, Integrated process, Heteroskedasticity
DOI:
http://dx.doi.org/10.1007/s00181-010-0440-1

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