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Ajuste Estacional e Integración en Variables Macroeconómicas

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  • Raimundo Soto

    () (Instituto de Economía)

Abstract

Separating seasonal components from other sources of economic fluctuations is crucial for both economic modeling and policy making. Practitioners treat seasonality as noise to be removed before estimating models and tend to apply deseasonalizing methods i

Suggested Citation

  • Raimundo Soto, 2002. "Ajuste Estacional e Integración en Variables Macroeconómicas," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 39(116), pages 135-155.
  • Handle: RePEc:ioe:cuadec:v:39:y:2002:i:116:p:135-155
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    References listed on IDEAS

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    1. Lee, Hahn S. & Siklos, Pierre L., 1995. "A note on the critical values for the maximum likelihood (seasonal) cointegration tests," Economics Letters, Elsevier, vol. 49(2), pages 137-145, August.
    2. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    3. Osborn, Denise R, et al, 1988. "Seasonality and the Order of Integration for Consumption," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 50(4), pages 361-377, November.
    4. Franses, Philip Hans & Hoek, Henk & Paap, Richard, 1997. "Bayesian analysis of seasonal unit roots and seasonal mean shifts," Journal of Econometrics, Elsevier, vol. 78(2), pages 359-380, June.
    5. Abeysinghe, Tilak, 1994. "Forecasting performance of seasonal-dummy models relative to some alternatives," Economics Letters, Elsevier, vol. 44(4), pages 365-370, April.
    6. Abeysinghe, Tilak, 1994. "Deterministic seasonal models and spurious regressions," Journal of Econometrics, Elsevier, vol. 61(2), pages 259-272, April.
    7. Joseph Beaulieu, J. & Miron, Jeffrey A., 1993. "Seasonal unit roots in aggregate U.S. data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 305-328.
    8. Miron, Jeffrey A & Beaulieu, J Joseph, 1996. "What Have Macroeconomists Learned about Business Cycles form the Study of Seasonal Cycles?," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 54-66, February.
    9. Sims, Christopher A., 1993. "Rational expectations modeling with seasonally adjusted data," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 9-19.
    10. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    11. Olekalns, Nilss, 1994. "Testing for unit roots in seasonally adjusted data," Economics Letters, Elsevier, vol. 45(3), pages 273-279.
    12. Abeysinghe, Tilak, 1991. "Inappropriate use of seasonal dummies in regression," Economics Letters, Elsevier, vol. 36(2), pages 175-179, June.
    13. Franses, Ph.H.B.F. & de Bruin, P. & van Dijk, D.J.C., 2000. "Seasonal smooth transition autoregression," Econometric Institute Research Papers EI 2000-06/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Ghysels, Eric, 1997. "On seasonality and business cycle durations: A nonparametric investigation," Journal of Econometrics, Elsevier, vol. 79(2), pages 269-290, August.
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    Cited by:

    1. Rómulo A.Chumacero & Francisco A.Gallego, 2002. "Trends and cycles in real-time," Estudios de Economia, University of Chile, Department of Economics, vol. 29(2 Year 20), pages 211-229, December.

    More about this item

    Keywords

    Seasonal unit roots; estimation; time series models;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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