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Forecasting industrial production using models with business cycle asymmetry Author info | Abstract | Publisher info | Download info | Related research | Statistics Chan Huh
This paper exploits an observed business cycle asymmetry, namely, a systematic shift in the dynamic relationship between output growth and an index for financial market conditions across expansionary and contractionary periods, to forecast monthly growth in industrial production. A bivariate model of monthly industrial production and the spread between the yield on 10-year Treasury notes and the federal funds rate is used as an example. This paper's method does not require a forecaster to make an exact exante determination of turning points in the output series being forecasted. A comparison of the forecast performance of various two-regime nonlinear and conventional linear models suggests that a measureable gain can be made by considering models which explicitly incorporate asymmetry in data.
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Article provided by Federal Reserve Bank of San Francisco in its journal Economic Review .
Volume (Year): (1998)
Issue (Month): ()
Pages: 29-41
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Keywords: Business cycles ; Industrial productivity ; Econometric models ; Other versions of this item:
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references Cited by : (explanations , 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.)
Jörg Döpke & Christian Pierdzioch, 2004.
"Politics and the Stock Market Evidence from Germany ,"
Kiel Working Papers
1203, Kiel Institute for the World Economy.
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Bruno Giancarlo & Lupi Claudio, 2003.
"Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data ,"
ISAE Working Papers
33, ISAE - Institute for Studies and Economic Analyses - (Rome, ITALY).
[Downloadable!]
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