Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index
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This paper investigates whether using natural logarithms (logs) of price indices for forecasting inflation rates is preferable to employing the original series. Univariate forecasts for annual inflation rates for a number of European countries and the USA based on monthly seasonal consumer price indices are considered. Stochastic seasonality and deterministic seasonality models are used. In many cases, the forecasts based on the original variables result in substantially smaller root mean squared errors than models based on logs. In turn, if forecasts based on logs are superior, the gains are typically small. This outcome sheds doubt on the common practice in the academic literature to forecast inflation rates based on differences of logs.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
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- Periodicity, Non-stationarity, and Forecasting of Economic and Financial Time Series: Editors' Introduction
- Consideration of Trends in Time Series
- Detecting Common Dynamics in Transitory Components
- Nonparametric Tests for Periodic Integration
- Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots
- Econometric Modelling of Time Series with Outlying Observations
- Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index
- Evaluating Automatic Model Selection
- On a Graphical Technique for Evaluating Some Rational Expectations Models
- Modeling the Volatility-Return Trade-Off When Volatility May Be Nonstationary
- HYBRID GARCH Models and Intra-Daily Return Periodicity
Articles in the same Issue
- Article
- Periodicity, Non-stationarity, and Forecasting of Economic and Financial Time Series: Editors' Introduction
- Consideration of Trends in Time Series
- Detecting Common Dynamics in Transitory Components
- Nonparametric Tests for Periodic Integration
- Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots
- Econometric Modelling of Time Series with Outlying Observations
- Forecasting Annual Inflation with Seasonal Monthly Data: Using Levels versus Logs of the Underlying Price Index
- Evaluating Automatic Model Selection
- On a Graphical Technique for Evaluating Some Rational Expectations Models
- Modeling the Volatility-Return Trade-Off When Volatility May Be Nonstationary
- HYBRID GARCH Models and Intra-Daily Return Periodicity
