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Luetkepohl, Helmut
Xu, Fang
Year of Publication: 
Series/Report no.: 
CESifo working paper 2591
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. It is found that it depends on the data generation process whether the former or the latter are preferable. 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.
Autoregressive moving average process
forecast mean squared error
instantaneous transformation
integrated process
Document Type: 
Working Paper

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