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Forecasting Levels of log Variables in Vector Autoregressions

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Author Info
Gunnar Bårdsen and Helmut Lütkepohl () (Department of Economics, Norwegian University of Science and Technology)

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Abstract

Sometimes 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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File URL: http://www.svt.ntnu.no/iso/WP/2009/7_logVAR1.pdf
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Publisher Info
Paper provided by Department of Economics, Norwegian University of Science and Technology in its series Working Paper Series with number 10409.

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Length: 17 pages
Date of creation: 16 Jun 2009
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Handle: RePEc:nst:samfok:10409

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  1. Arino, Miguel A. & Franses, Philip Hans, 2000. "Forecasting the levels of vector autoregressive log-transformed time series," International Journal of Forecasting, Elsevier, vol. 16(1), pages 111-116. [Downloadable!] (restricted)
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This page was last updated on 2009-11-3.


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