IDEAS home Printed from https://ideas.repec.org/p/msh/ebswps/2001-2.html
   My bibliography  Save this paper

The Importance Of Common Cyclical Features in VAR Analysis: A Monte-Carlo Study

Author

Listed:
  • Vahid, F.

    ()

  • Issler, J.V.

Abstract

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models.

Suggested Citation

  • Vahid, F. & Issler, J.V., 2001. "The Importance Of Common Cyclical Features in VAR Analysis: A Monte-Carlo Study," Monash Econometrics and Business Statistics Working Papers 2/01, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:2001-2
    as

    Download full text from publisher

    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2001/wp2-01.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Issler, Joao Victor & Vahid, Farshid, 2001. "Common cycles and the importance of transitory shocks to macroeconomic aggregates," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 449-475, June.
    2. Vahid, F & Engle, Robert F, 1993. "Common Trends and Common Cycles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 341-360, Oct.-Dec..
    3. Zellner, Arnold & Hong, Chansik, 1989. "Forecasting international growth rates using Bayesian shrinkage and other procedures," Journal of Econometrics, Elsevier, vol. 40(1), pages 183-202, January.
    4. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : II. New directions," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 309-341.
    5. repec:fgv:epgrbe:v:47:n:2:a:1 is not listed on IDEAS
    6. Gerald Carlino & Keith Sill, 2001. "Regional Income Fluctuations: Common Trends And Common Cycles," The Review of Economics and Statistics, MIT Press, vol. 83(3), pages 446-456, August.
    7. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-380, October.
    8. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income and Interest Rates: Reinterpreting the Time Series Evidence," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 185-246 National Bureau of Economic Research, Inc.
    9. Gerald A. Carlino & Keith Sill, 1996. "Common trends and common cycles in regional per capita incomes," Working Papers 96-13, Federal Reserve Bank of Philadelphia.
    10. repec:fth:harver:1435 is not listed on IDEAS
    11. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-395, October.
    12. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    13. Lucas, Robert E., 1977. "Understanding business cycles," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 5(1), pages 7-29, January.
    14. Vahid, Farshid & Issler, Joao Victor, 2002. "The importance of common cyclical features in VAR analysis: a Monte-Carlo study," Journal of Econometrics, Elsevier, vol. 109(2), pages 341-363, August.
    15. repec:sbe:breart:v:18:y:1998:i:1:a:2841 is not listed on IDEAS
    16. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    17. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
    18. Issler, João Victor & Ferreira, Pedro Cavalcanti, 1998. "Time-series properties and empirical evidence of growth and infraestructure: revised version," FGV/EPGE Economics Working Papers (Ensaios Economicos da EPGE) 336, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
    19. Nickelsburg, Gerald, 1985. "Small-sample properties of dimensionality statistics for fitting VAR models to aggregate economic data : A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 28(2), pages 183-192, May.
    20. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    21. Granger, Clive W. J. & King, Maxwell L. & White, Halbert, 1995. "Comments on testing economic theories and the use of model selection criteria," Journal of Econometrics, Elsevier, vol. 67(1), pages 173-187, May.
    22. Engle, Robert F. & Issler, Joao Victor, 1995. "Estimating common sectoral cycles," Journal of Monetary Economics, Elsevier, vol. 35(1), pages 83-113, February.
    23. Clements, M.P. & Hendry, D.F., 1992. "Forecasting in Cointegrated Systems," Economics Series Working Papers 99139, University of Oxford, Department of Economics.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Reduced rank models; model selection criteria; forecasting; variance decomposition;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:msh:ebswps:2001-2. 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: (Dr Xibin Zhang) or (Joanne Lustig). General contact details of provider: http://edirc.repec.org/data/dxmonau.html .

    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 CitEc recognized a reference but did not link an item in RePEc 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 RePEc Author Service 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.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.