Does Noncausality Help in Forecasting Economic Time Series?

Markku Lanne, Henri Nyberg, Erkka Saarinen

Research output: Contribution to journalArticlepeer-review


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
Issue number4
Pages (from-to)2849-2859
Number of pages11
Publication statusPublished - Oct 2012
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 511 Economics

Cite this