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Estimating Structural Change with Smooth Transition Regressions: an Application to Meat Demand

  • Holt, Matthew T.
  • Balagtas, Joseph V.

This paper explores the role of structural change in systems of demand equations. Specifically, we adapt the time—varying regression framework of Lin and Teräsvirta (1994), which in turn is related to the dynamic smooth transition models introduced by Teräsvirta (1994). Unlike previous efforts at modeling structural change in demand systems, we do not impose the nature of the change to be monotonic—several non-monotonic alternatives are considered. An application is presented using the Almost Ideal Inverse Demand System (IAIDS) applied to U.S. meat demand data, 1960-2004. Results show the importance of modeling structural change and that, moreover, the best-fitting model is associated with a form of symmetric, non-monotonic structural change.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 15331.

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Date of creation: 20 May 2009
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Handle: RePEc:pra:mprapa:15331
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  1. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  2. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
  3. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-30, March.
  4. Eales, James S. & Unnevehr, Laurian J., 1994. "The inverse almost ideal demand system," European Economic Review, Elsevier, vol. 38(1), pages 101-115, January.
  5. Dahlgran, Roger A., 1987. "Complete Flexibility Systems And The Stationarity Of U.S. Meat Demands," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 12(02), December.
  6. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  7. Holt, Matthew T., 2002. "Inverse demand systems and choice of functional form," European Economic Review, Elsevier, vol. 46(1), pages 117-142, January.
  8. Holt, Matthew T & Goodwin, Barry K, 1997. "Generalized Habit Formation in an Inverse Almost Ideal Demand System: An Application to Meat Expenditures in the U.S," Empirical Economics, Springer, vol. 22(2), pages 293-320.
  9. Seo, Myunghwan, 2006. "Bootstrap testing for the null of no cointegration in a threshold vector error correction model," Journal of Econometrics, Elsevier, vol. 134(1), pages 129-150, September.
  10. Alston, Julian M. & Chalfant, James A., 1991. "Can We Take The Con Out Of Meat Demand Studies?," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 16(01), July.
  11. Pollak, R.A. & Wales, T.J., 1990. "The Likelihood Dominance Criterion: A New Approach To Model Selection," Working Papers 90-10, University of Washington, Department of Economics.
  12. George C. Davis, 1997. "The Logic of Testing Structural Change in Meat Demand: A Methodological Analysis and Appraisal," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(4), pages 1186-1192.
  13. Davis, George C., 1997. "The Formal Logic Of Testing Structural Change In Meat Demand: A Methodological Analysis," Faculty Paper Series 23975, Texas A&M University, Department of Agricultural Economics.
  14. Barten, A. P. & Bettendorf, L. J., 1989. "Price formation of fish : An application of an inverse demand system," European Economic Review, Elsevier, vol. 33(8), pages 1509-1525, October.
  15. Farley, John U. & Hinich, Melvin & McGuire, Timothy W., 1975. "Some comparisons of tests for a shift in the slopes of a multivariate linear time series model," Journal of Econometrics, Elsevier, vol. 3(3), pages 297-318, August.
  16. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
  17. Goodwin, Barry K. & Harper, Daniel C. & Schnepf, Randall D., 2000. "Short-Run Demand Relationships In The U.S. Fats And Oils Complex," 2000 Conference, April 17-18 2000, Chicago, Illinois 18942, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  18. Holt, Matthew T., 1998. "Autocorrelation specification in singular equation systems: A further look," Economics Letters, Elsevier, vol. 58(2), pages 135-141, February.
  19. Skalin, Joakim, 1998. "Testing linearity against smooth transition autoregression using a parametric bootstrap," SSE/EFI Working Paper Series in Economics and Finance 276, Stockholm School of Economics, revised 13 Dec 1998.
  20. Henry L. Bryant & George C. Davis, 2008. "Revisiting Aggregate U.S. Meat Demand with a Bayesian Averaging of Classical Estimates Approach: Do We Need a More General Theory?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(1), pages 103-116.
  21. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.
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