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Rational expectations modeling with seasonally adjusted data

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  • Sims, Christopher A.

Abstract

In a world where time series show clear seasonal fluctuations, rational agents will take account of those fluctuations in planning their own behavior. Using seasonally adjusted data to model behavior of such agents throws away information and introduces possibly severe bias. Nonetheless it may be true fairly often that rational expectations modeling with seasonally adjusted data, treating the adjusted data as if it were actual data, gives approximately correct results; and naive extensions of standard modeling techniques to seasonally unadjusted data may give worse results than naive use of adjusted data. This paper justifies these claims with examples and detailed arguments.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 55 (1993)
Issue (Month): 1-2 ()
Pages: 9-19

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Handle: RePEc:eee:econom:v:55:y:1993:i:1-2:p:9-19

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Web page: http://www.elsevier.com/locate/jeconom

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Cited by:
  1. Norrbin, Stefan C. & Reffett, Kevin L., 1996. "A substitution test of long-run money demand," Journal of Macroeconomics, Elsevier, vol. 18(2), pages 253-270.
  2. Rae, David, 1996. "NBNZ-DEMONZ: A dynamic equilibrium model of New Zealand," Economic Modelling, Elsevier, vol. 13(1), pages 91-165, January.
  3. Christiano, Lawrence J. & Todd, Richard M., 2002. "The conventional treatment of seasonality in business cycle analysis: does it create distortions?," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 335-364, March.
  4. Eric Ghysels, 1992. "Christmas, Spring and the Dawning of Economic Recovery," Cowles Foundation Discussion Papers 1027, Cowles Foundation for Research in Economics, Yale University.
  5. Berkowitz, Jeremy, 2001. "Generalized spectral estimation of the consumption-based asset pricing model," Journal of Econometrics, Elsevier, vol. 104(2), pages 269-288, September.
  6. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
  7. Raimundo Soto, 2000. "Ajuste Estacional e Integración en Variables Macroeconómicas," Working Papers Central Bank of Chile 73, Central Bank of Chile.
  8. Lars Peter Hansen & Thomas J. Sargent, 2001. "Acknowledging Misspecification in Macroeconomic Theory," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 4(3), pages 519-535, July.
  9. T. Hutchison & I. Pellengahr & K. Podczeck & R. Noll & I. Vogelsang & B. Mitchell & S. Martin & J. Mairesse, 1994. "Book review," Journal of Economics, Springer, vol. 59(3), pages 325-349, October.
  10. Ghysels, Éric, 1994. "L’analyse économétrique et la saisonnalité," L'Actualité Economique, Société Canadienne de Science Economique, vol. 70(1), pages 43-62, mars.
  11. Braun, R Anton & Evans, Charles L, 1998. "Seasonal Solow Residuals and Christmas: A Case for Labor Hoarding and Increasing Returns," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 30(3), pages 306-30, August.
  12. Olalla, Myriam García & Gómez, Alejandro Ruiz, 2011. "Robust control and central banking behaviour," Economic Modelling, Elsevier, vol. 28(3), pages 1265-1278, May.
  13. Norrbin, S.C. & Reffett, K.L., 1993. "Trade Credit in a Monetary Economy," Working Papers 1993_06_02, Department of Economics, Florida State University.
  14. Otrok, Christopher & Ravikumar, B. & Whiteman, Charles H., 2007. "A generalized volatility bound for dynamic economies," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2269-2290, November.
  15. Zhongjun Qu & Denis Tkachenko, 2011. "Frequency Domain Analysis of Medium Scale DSGE Models with Application to Smets and Wouters (2007)," Boston University - Department of Economics - Working Papers Series WP2011-060, Boston University - Department of Economics.

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