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Dynamic Analysis With Time Series Models: Simulation And Empirical Evidence

  • Robledo, Carlos W.
  • Zapata, Hector O.
Registered author(s):

    The performance of the FPE, AIC, HQ and SC criteria in choosing lag-length, and the effect on the impulse-response functions, are studied in a Monte Carlo simulation. The experiments include stationary, cointegrated, and mixed unit root VAR and MA cases.

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    File URL: http://purl.umn.edu/21526
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    Paper provided by American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association) in its series 1999 Annual meeting, August 8-11, Nashville, TN with number 21526.

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    Date of creation: 1999
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    Handle: RePEc:ags:aaea99:21526
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    1. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-42, October.
    2. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer, vol. 21(1), pages 243-247, December.
    3. Lutkepohl, Helmut & Reimers, Hans-Eggert, 1992. "Impulse response analysis of cointegrated systems," Journal of Economic Dynamics and Control, Elsevier, vol. 16(1), pages 53-78, January.
    4. Peter C.B. Phillips, 1995. "Impulse Response and Forecast Error Variance Asymptotics in Nonstationary VAR's," Cowles Foundation Discussion Papers 1102, Cowles Foundation for Research in Economics, Yale University.
    5. Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
    6. Spencer, David E, 1989. "Does Money Matter? The Robustness of Evidence from Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 21(4), pages 442-54, November.
    7. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
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