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

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  • 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
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    File URL: http://www.buseco.monash.edu.au/ebs/pubs/wpapers/2001/wp2-01.pdf
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    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, EPGE Brazilian School of Economics and Finance - FGV EPGE (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.
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    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

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