Testing for common cycles in non-stationary VARs with varied frecquency data
This paper proposes a new way for detecting the presence of common cyclical featureswhen several time series are observed/sampled at different frequencies, hence generalizingthe common-frequency approach introduced by Engle and Kozicki 1993 and Vahid andEngle 1993. We start with the mixed-frequency VAR representation investigated in Ghysels2012 for stationary time series. For non-stationary time series in levels, we showthat one has to account for the presence of two sets of long-run relationships. The First setis implied by identities stemming from the fact that the differences of the high-frequencyI1 regressors are stationary. The second set comes from possible additional long-run relationshipsbetween one of the high-frequency series and the low-frequency variables. Ourtransformed VECM representations extend the results of Ghysels 2012 and are very importantfor determining the correct set of variables to be used in a subsequent commoncycle investigation. This has some empirical implications both for the behavior of the teststatistics as well as for forecasting. Empirical analyses with the quarterly real GNP andmonthly industrial production indices for, respectively, the U.S. and Germany illustrate ournew approach. This is also investigated in a Monte Carlo study, where we compare our proposedmixed-frequency models with models stemming from classical temporal aggregationmethods.
|Date of creation:||2013|
|Contact details of provider:|| Postal: P.O. Box 616, 6200 MD Maastricht|
Phone: +31 (0)43 38 83 830
Web page: http://www.maastrichtuniversity.nl/
More information through EDIRC
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.:
- Andrea Silvestrini & David Veredas, 2008.
"Temporal aggregation of univariate and multivariate time series models: a survey,"
ULB Institutional Repository
2013/136205, ULB -- Universite Libre de Bruxelles.
- Andrea Silvestrini & David Veredas, 2008. "Temporal Aggregation Of Univariate And Multivariate Time Series Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 22(3), pages 458-497, 07.
- Andrea Silvestrini & David Veredas, 2008. "Temporal aggregation of univariate and multivariate time series models: A survey," Temi di discussione (Economic working papers) 685, Bank of Italy, Economic Research and International Relations Area.
- SILVESTRINI, Andrea & VEREDAS, David, "undated". "Temporal aggregation of univariate and multivariate time series models: A survey," CORE Discussion Papers RP 2013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Warne, A., 1993. "A Common Trends Model: Identification, Estimation and Inference," Papers 555, Stockholm - International Economic Studies.
- J. Isaac Miller, 2011. "Cointegrating MiDaS Regressions and a MiDaS Test," Working Papers 1104, Department of Economics, University of Missouri.
- Zellner, Arnold & Palm, Franz, 1974.
"Time series analysis and simultaneous equation econometric models,"
Journal of Econometrics,
Elsevier, vol. 2(1), pages 17-54, May.
- ZELLNER, Arnold & PALM, Franz, "undated". "Time series analysis and simultaneous equation econometric models," CORE Discussion Papers RP 173, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Zadrozny, Peter, 1988. "Gaussian Likelihood of Continuous-Time ARMAX Models When Data Are Stocks and Flows at Different Frequencies," Econometric Theory, Cambridge University Press, vol. 4(01), pages 108-124, April.
When requesting a correction, please mention this item's handle: RePEc:unm:umagsb:2013002. 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: (Leonne Portz)
If references are entirely missing, you can add them using this form.