Forecasting Levels of log Variables in Vector Autoregressions
AbstractSometimes forecasts of the original variable are of interest al- though a variable appears in logarithms (logs) in a system of time series. In that case converting the forecast for the log of the variable to a naive forecast of the original variable by simply applying the exponential transformation is not optimal theoretically. A simple expression for the optimal forecast un- der normality assumptions is derived. Despite its theoretical advantages the optimal forecast is shown to be inferior to the naive forecast if speci¯cation and estimation uncertainty are taken into account. Hence, in practice using the exponential of the log forecast is preferable to using the optimal forecast.
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Bibliographic InfoPaper provided by Department of Economics, Norwegian University of Science and Technology in its series Working Paper Series with number 10409.
Length: 17 pages
Date of creation: 16 Jun 2009
Date of revision:
Other versions of this item:
- Bårdsen, Gunnar & Lütkepohl, Helmut, 2011. "Forecasting levels of log variables in vector autoregressions," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1108-1115, October.
- Gunnar Bardsen & Helmut Luetkepohl, 2009. "Forecasting Levels of log Variables in Vector Autoregressions," Economics Working Papers ECO2009/24, European University Institute.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-07-03 (All new papers)
- NEP-ECM-2009-07-03 (Econometrics)
- NEP-ETS-2009-07-03 (Econometric Time Series)
- NEP-FOR-2009-07-03 (Forecasting)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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