The role of the log transformation in forecasting economic variables

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...

Full description

Saved in:
Bibliographic Details
Published in:Empirical economics 2012-06, Vol.42 (3), p.619-638
Main Authors: Lütkepohl, Helmut, Xu, Fang
Format: Article
Language:English
Subjects:
Analysis
Econometrics
Economic theory
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Economics and Finance
Finance
Forecasting
Insurance
Investigations
Management
Mean square errors
Regression analysis
Statistics for Business
Studies
Time series
Variables
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0377-7332
1435-8921
DOI:10.1007/s00181-010-0440-1