Forecasting with a noncausal VAR model
Simulation-based forecasting methods for a non-Gaussian noncausal vector autoregressive (VAR) model are proposed. In noncausal autoregressions the assumption of non-Gaussianity is needed for reasons of identifiability. Unlike in conventional causal autoregressions the prediction problem in noncausal autoregressions is generally nonlinear, implying that its analytical solution is unfeasible and, therefore, simulation or numerical methods are required in computing forecasts. It turns out that different special cases of the model call for different simulation procedures. Monte Carlo simulations demonstrate that gains in forecasting accuracy are achieved by using the correct noncausal VAR model instead of its conventional causal counterpart. In an empirical application, a noncausal VAR model comprised of U.S. inflation and marginal cost turns out superior to the best-fitting conventional causal VAR model in forecasting inflation.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
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.:
- Lanne, Markku & Luoto, Jani, 2013.
"Autoregression-based estimation of the new Keynesian Phillips curve,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 37(3), pages 561-570.
- Lanne, Markku & Luoto, Jani, 2011. "Autoregression-Based Estimation of the New Keynesian Phillips Curve," MPRA Paper 29801, University Library of Munich, Germany.
- James M. Nason & Gregor W. Smith, 2005.
"Identifying the New Keynesian Phillips Curve,"
1026, Queen's University, Department of Economics.
- John Geweke, 1995.
"Monte Carlo simulation and numerical integration,"
192, Federal Reserve Bank of Minneapolis.
- Lanne, Markku & Saikkonen, Pentti, 2010.
"Noncausal autoregressions for economic time series,"
32943, University Library of Munich, Germany.
- Lanne Markku & Saikkonen Pentti, 2011. "Noncausal Autoregressions for Economic Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
- Lanne, Markku & Luoma, Arto & Luoto, Jani, 2009.
"Bayesian Model Selection and Forecasting in Noncausal Autoregressive Models,"
23646, University Library of Munich, Germany.
- Markku Lanne & Arto Luoma & Jani Luoto, 2012. "Bayesian Model Selection And Forecasting In Noncausal Autoregressive Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(5), pages 812-830, 08.
- Lanne, Markku & Saikkonen, Pentti, 2013.
"Noncausal Vector Autoregression,"
Cambridge University Press, vol. 29(03), pages 447-481, June.
- Athanasopoulos, George & Vahid, Farshid, 2008.
"VARMA versus VAR for Macroeconomic Forecasting,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 26, pages 237-252, April.
- George Athanasopoulos & Farshid Vahid, 2006. "VARMA versus VAR for Macroeconomic Forecasting," Monash Econometrics and Business Statistics Working Papers 4/06, Monash University, Department of Econometrics and Business Statistics.
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Deborah Gefang & Gary Koop & Simon Potter, 2011.
"The Dynamics of UK and US Inflation Expectations,"
1120, University of Strathclyde Business School, Department of Economics.
- Gefang, Deborah & Koop, Gary & Potter, Simon M., 2012. "The Dynamics of UK and US Inflation Expectation," SIRE Discussion Papers 2012-46, Scottish Institute for Research in Economics (SIRE).
- Gefang, Deborah & Koop, Gary & Potter, Simon M., 2008. "The Dynamics of UK and US Inflation Expectations," SIRE Discussion Papers 2008-59, Scottish Institute for Research in Economics (SIRE).
- Deborah Gefang & Gary Koop & Simon M. Potter, 2009. "The Dynamics of UK and US Inflation Expectations," Working Paper Series 14_09, The Rimini Centre for Economic Analysis, revised Jan 2009.
- Gefang, Deborah & Koop, Gary & Potter, Simon M., 2011. "The Dynamics of UK and US Inflation Expectations," SIRE Discussion Papers 2011-47, Scottish Institute for Research in Economics (SIRE).
- repec:att:wimass:9417 is not listed on IDEAS
- Henri Nyberg & Markku Lanne & Erkka Saarinen, 2012. "Does noncausality help in forecasting economic time series?," Economics Bulletin, AccessEcon, vol. 32(4), pages 2849-2859.
- Canova, Fabio, 2007. "G-7 Inflation Forecasts: Random Walk, Phillips Curve Or What Else?," Macroeconomic Dynamics, Cambridge University Press, vol. 11(01), pages 1-30, February.
- Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
- Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2010.
"Optimal Forecasting of Noncausal Autoregressive Time Series,"
23648, University Library of Munich, Germany.
- Lanne, Markku & Luoto, Jani & Saikkonen, Pentti, 2012. "Optimal forecasting of noncausal autoregressive time series," International Journal of Forecasting, Elsevier, vol. 28(3), pages 623-631.
- Lof, Matthijs, 2011.
"Noncausality and Asset Pricing,"
30519, University Library of Munich, Germany.
- West, Kenneth D, 1996.
"Asymptotic Inference about Predictive Ability,"
Econometric Society, vol. 64(5), pages 1067-84, September.
- Breid, F. Jay & Davis, Richard A. & Lh, Keh-Shin & Rosenblatt, Murray, 1991. "Maximum likelihood estimation for noncausal autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 36(2), pages 175-198, February.
When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:76:y:2014:i:c:p:536-555. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.