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The Role of log Transformation in Forecasting Economic Variables

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MWP_2009_06.pdf (231.65 KB)
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https://hdl.handle.net/1814/11150
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1830-7728
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2009
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Working Paper
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Autoregressive moving average process; Forecast mean squared error; Instantaneous transformation; Integrated process; Heteroskedasticity; C22
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http://hdl.handle.net/1814/31057
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EUI MWP; 2009/06
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LUETKEPOHL, Helmut, XU, Fang, The Role of log Transformation in Forecasting Economic Variables, EUI MWP, 2009/06 - https://hdl.handle.net/1814/11150
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. 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.
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European University Institute
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