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Seasonality in Regression: An Application of Smoothness Priors

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  • Mark Gersovitz
  • James G. MacKinnon

Abstract

This article argues that conventional approaches to the treatment of seasonality in econometric investigation are often inappropriate. A more appropriate technique is to allow all regression coefficients to vary with the season, but to constrain them to do so in a smooth fashion. A Bayesian method of estimating smoothly varying seasonal coefficients is developed, based on Shiller's (1973) approach to estimating distributed lags. In a sampling experiment, this technique outperforms ordinary least squares by a substantial margin. An application of this technique to the estimation of the demand for soft drinks is also presented.

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File URL: http://qed.econ.queensu.ca/working_papers/papers/qed_wp_257.pdf
File Function: First version 1977
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Bibliographic Info

Paper provided by Queen's University, Department of Economics in its series Working Papers with number 257.

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Length: 20
Date of creation: 1977
Date of revision:
Publication status: Published in Journal of the American Statistical Association, 73, 1978
Handle: RePEc:qed:wpaper:257

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Related research

Keywords: seasonality; smoothness prior; distributed lag; mixed estimation; soft drinks;

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References

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  1. Michael C. Lovell, 1963. "Seasonal Adjustment of Economic Time Series and Multiple Regression," Cowles Foundation Discussion Papers 151, Cowles Foundation for Research in Economics, Yale University.
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Citations

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Cited by:
  1. Svend Hylleberg, 2006. "Seasonal Adjustment," Economics Working Papers 2006-04, School of Economics and Management, University of Aarhus.
  2. Rodríguez Poo, Juan M. & Ferreira García, María Eva & Orbe Mandaluniz, Susan, 2001. "Nonparametric estimation of time varying parameters under shape restrictions," BILTOKI 2001-02, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
  3. Richard M. Todd, 1989. "Periodic linear-quadratic methods for modeling seasonality," Staff Report 127, Federal Reserve Bank of Minneapolis.
  4. Robert J. Shiller, 1982. "Smoothness Priors and Nonlinear Regression," NBER Technical Working Papers 0025, National Bureau of Economic Research, Inc.

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