Does Noncausality Help in Forecasting Economic Time Series?

Markku Lanne, Henri Nyberg, Erkka Saarinen

Research output: Contribution to journalArticleScientificpeer-review

Abstract

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.
Original languageEnglish
JournalEconomics Bulletin
Volume32
Issue number4
Pages (from-to)2849-2859
Number of pages11
ISSN1545-2921
Publication statusPublished - Oct 2012
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 511 Economics

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