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Forecasting with the almost ideal demand system: evidence from some alternative dynamic specifications

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  • Marcus Chambers
  • K. Ben Nowman

Abstract

The almost ideal demand system is used as a representation of long run demands in discrete time and continuous time error correction models to produce forecasts of budget shares beyond the sample period. The estimated models are subjected to a battery of tests, and an analysis of the forecasts indicates that continuous time adjustment mechanisms, based around fully modified estimates of the long run preference parameters, provide a remarkably accurate method of forecasting budget shares.

Suggested Citation

  • Marcus Chambers & K. Ben Nowman, 1997. "Forecasting with the almost ideal demand system: evidence from some alternative dynamic specifications," Applied Economics, Taylor & Francis Journals, vol. 29(7), pages 935-943.
  • Handle: RePEc:taf:applec:v:29:y:1997:i:7:p:935-943
    DOI: 10.1080/000368497326598
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    Cited by:

    1. Chia-Lin Chang & Thanchanok Khamkaew & Michael McAleer, 2010. "Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia," CIRJE F-Series CIRJE-F-735, CIRJE, Faculty of Economics, University of Tokyo.
    2. Balcombe, Kelvin & Bailey, Alastair, 2006. "Bayesian inference of a smooth transition dynamic almost ideal model of food demand in the US," MPRA Paper 17305, University Library of Munich, Germany.
    3. M. Hashem Pesaran & Yongcheol Shin, 2002. "Long-Run Structural Modelling," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 49-87.
    4. Chang, Hui-Shung (Christie) & Bettington, Nicholas, 2001. "Demand for Wine in Australia: Systems Versus Single Equation Approach," Working Papers 12923, University of New England, School of Economics.
    5. Wang, Zijun & Bessler, David A, 2002. "The Homogeneity Restriction and Forecasting Performance of VAR-Type Demand Systems: An Empirical Examination of US Meat Consumption," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(3), pages 193-206, April.
    6. Chang, Hui-Shung & Griffith, Garry & Bettington, Nicholas, 2002. "The Demand for Wine in Australia Using a Systems Approach: Industry Implications," Australasian Agribusiness Review, University of Melbourne, Melbourne School of Land and Environment, vol. 10.
    7. J. M. Gil & B. Dhehibi & M. Ben Kaabia & A. M. Angulo, 2004. "Non-stationarity and the import demand for virgin olive oil in the European Union," Applied Economics, Taylor & Francis Journals, vol. 36(16), pages 1859-1869.
    8. Li, Gang & Song, Haiyan & Witt, Stephen F., 2006. "Time varying parameter and fixed parameter linear AIDS: An application to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 22(1), pages 57-71.
    9. Chang, Hui-Shung (Christie), 2000. "An econometric analysis of the competitive position of Australian cotton in the Japanese market," Working Papers 12940, University of New England, School of Economics.
    10. Byers, S. L. & Nowman, K. B., 1998. "Forecasting U.K. and U.S. interest rates using continuous time term structure models," International Review of Financial Analysis, Elsevier, vol. 7(3), pages 191-206.
    11. Tonsor, Glynn T. & Marsh, Thomas L., 2005. "Comparing Heterogeneous Consumption in US and Japanese Meat and Fish Demand," 2005 Annual meeting, July 24-27, Providence, RI 19567, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. repec:eee:touman:v:45:y:2014:i:c:p:159-170 is not listed on IDEAS

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