Does noncausality help in forecasting economic time series?

Economics Bulletin

Volumn 32, Issue 4, 2012, Pages 2849-2859

  Nyberg, Henri ^a   Lanne, Markku ^a   Saarinen, Erkka ^a  

^a UNIVERSITY OF HELSINKI   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84873432219     PISSN: None     EISSN: 15452921     Source Type: Journal    
DOI: None     Document Type: Article

References (8)

1. Breidt, J, Davis, R.A, Lii, K.S, and M. Rosenblatt (1991) "Maximum likeli-hood estimation for noncausal autoregressive processes".Journal of Multivari-ate Analysis 36, 175-198.
2. Diebold, F.X, and R.Mariano (1995)."Comparing predictive accuracy".Journal of Business and Economic Statistics 13, 253-263.
3. Lanne, M, and P. Saikkonen (2011)."Noncausal autoregressions for economic time series".Journal of Time Series Econometrics 3, article 2.
4. Lanne, M, Luoma, A, and J. Luoto (2012) ."Bayesian model selection and fore-casting in noncausal autoregressive models".Journal of Applied Econometrics 27, 812-830
5. Lanne, M, Luoto, J, and P. Saikkonen (2012) ."Optimal forecasting of noncausal autoregressive time series".International Journal of Forecasting 28, 623-631.
6. Lanne,M, Nyberg, H, and E. Saarinen (2011) ."Forecasting U.S. macroeconomic and .nancial time series with noncausal and causal AR models: A comparison". HECER Discussion Paper, No. 319
7. Marcellino, M, Stock, J.H, and M.W. Watson (2006). "A comparison of direct and iterated AR methods for forecasting macroeconomic time series".Journal of Econometrics 135, 499-526.
8. Rosenblatt, M. (2000) "Gaussian and Non-Gaussian Linear Time Series and Random Fields", Springer-Verlag: New York.