IDEAS home Printed from
MyIDEAS: Login to save this article or follow this journal

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

  • Matthew T. Holt
  • Joseph V. Balagtas

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.

(This abstract was borrowed from another version of this item.)

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.

Volume (Year): 91 (2009)
Issue (Month): 5 ()
Pages: 1424-1431

in new window

Handle: RePEc:oup:ajagec:v:91:y:2009:i:5:p:1424-1431
Contact details of provider: Postal: 555 East Wells Street, Suite 1100, Milwaukee, Wisconsin 53202
Phone: (414) 918-3190
Fax: (414) 276-3349
Web page:

More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. 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.
  2. 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.
  3. 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.
  4. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-26, June.
  5. 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.
  6. Pollak, Robert A. & Wales, Terence J., 1991. "The likelihood dominance criterion : A new approach to model selection," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 227-242, February.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. Holt, Matthew T., 2002. "Inverse demand systems and choice of functional form," European Economic Review, Elsevier, vol. 46(1), pages 117-142, January.
  12. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  13. Eales, James S. & Unnevehr, Laurian J., 1994. "The inverse almost ideal demand system," European Economic Review, Elsevier, vol. 38(1), pages 101-115, January.
  14. 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.
  15. Donald W.K. Andrews & Werner Ploberger, 1992. "Optimal Tests When a Nuisance Parameter Is Present Only Under the Alternative," Cowles Foundation Discussion Papers 1015, Cowles Foundation for Research in Economics, Yale University.
  16. Holt, Matthew T., 1998. "Autocorrelation specification in singular equation systems: A further look," Economics Letters, Elsevier, vol. 58(2), pages 135-141, February.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:oup:ajagec:v:91:y:2009:i:5:p:1424-1431. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Oxford University Press)

or (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.