The Role of log Transformation in Forecasting Economic Variables
Title: The Role of log Transformation in Forecasting Economic Variables
Publisher: European University Institute
Series/Report no.: EUI MWP; 2009/06
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.
Subject: Autoregressive moving average process; forecast mean squared error; instantaneous transformation; integrated process; heteroskedasticity; C22
Type of Access: openAccess
Final published version: http://hdl.handle.net/1814/31057