Does noncausality help in forecasting economic time series?
Markku Lanne and
Erkka Saarinen ()
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Erkka Saarinen: University of Helsinki
Economics Bulletin, 2012, vol. 32, issue 4, 2849-2859
In this paper, we compare the forecasting performance of univariate noncausal and conventional causal autoregressive models for a comprehensive data set consisting of 170 monthly U.S. macroeconomic and financial time series. The noncausal models consistently outperform the causal models. For a collection of quarterly time series, the improvement in forecast accuracy due to allowing for noncausality is found even greater.
Keywords: Noncausal autoregression; forecast comparison; macroeconomic variables; financial variables (search for similar items in EconPapers)
JEL-codes: C2 C5 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ebl:ecbull:eb-12-00360
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