IDEAS home Printed from https://ideas.repec.org/p/ags/aaea11/103736.html
   My bibliography  Save this paper

Comparison of several demand systems

Author

Listed:
  • Meyer, Stefan
  • Yu, Xiaohua
  • Abler, David G.

Abstract

Using Monte-Carlo simulation, , we compare the most popular demand systems including the LES, AIDS, BTL, QES, QUAIDS and AIDADS, and find that different models actually have different advantages in estimating different elasticities. Specifically, QES, AIDS and AIDADS models are the best in income, own-price and cross-price elasticities, respectively. Overall, AIDADS model has the best performance. The results indicate that the rank three models are not necessary always better than the rank two models.

Suggested Citation

  • Meyer, Stefan & Yu, Xiaohua & Abler, David G., 2011. "Comparison of several demand systems," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103736, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea11:103736
    DOI: 10.22004/ag.econ.103736
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/103736/files/Meyer_Yu_Abler_simulation1.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.103736?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Giancarlo Moschini & Karl D. Meilke, 1989. "Modeling the Pattern of Structural Change in U.S. Meat Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(2), pages 253-261.
    2. James Banks & Richard Blundell & Arthur Lewbel, 1997. "Quadratic Engel Curves And Consumer Demand," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 527-539, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ngueuleweu Tiwang, Gildas, 2020. "Ph.D in Economics, Option Agricultural Economics," MPRA Paper 99798, University Library of Munich, Germany, revised 2020.
    2. Bouët, Antoine & Femenia, Fabienne & Laborde, David, 2014. "On the role of demand systems in CGE simulations of trade reforms," Conference papers 332443, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    3. Zhou, De & Yu, Xiaohua & Abler, David & Chen, Danhong, 2020. "Projecting meat and cereals demand for China based on a meta-analysis of income elasticities," China Economic Review, Elsevier, vol. 59(C).
    4. Widenhorn, Andreas & Salhofer, Klaus, 2014. "Using a Generalized Differenced Demand Model to Estimate Price and Expenditure Elasticities for Milk and Meat in Austria," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 63(02), pages 1-16, June.
    5. Colchero, M.A. & Salgado, J.C. & Unar-Munguía, M. & Hernández-Ávila, M. & Rivera-Dommarco, J.A., 2015. "Price elasticity of the demand for sugar sweetened beverages and soft drinks in Mexico," Economics & Human Biology, Elsevier, vol. 19(C), pages 129-137.
    6. Widenhorn, Andreas & Salhofer, Klaus, 2014. "Using a Generalized Differenced Demand Model to Estimate Price and Expenditure Elasticities for Milk and Meat in Austria," Journal of International Agricultural Trade and Development, Journal of International Agricultural Trade and Development, vol. 63(2).
    7. Sanvi Avouyi-Dovi & Christian Pfister & Franck Sédillot, 2019. "French Households’ Portfolio: The Financial Almost Ideal Demand System Appraisal," Working papers 728, Banque de France.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vardges Hovhannisyan & Brian W. Gould, 2014. "Structural change in urban Chinese food preferences," Agricultural Economics, International Association of Agricultural Economists, vol. 45(2), pages 159-166, March.
    2. Sulgham, Anil K. & Zapata, Hector O., 2006. "A Dynamic Approach to Estimate Theoretically Consistent US Meat Demand System," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35441, Southern Agricultural Economics Association.
    3. Toshinobu Matsuda, 2006. "Linear approximations to the quadratic almost ideal demand system," Empirical Economics, Springer, vol. 31(3), pages 663-675, September.
    4. Steven D. Silver, 2016. "A QUAIDS Model of Need-Based Structure in U.S. Personal Consumption 2006–2012," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 44(3), pages 303-323, September.
    5. Vardges Hovhannisyan & Brian W. Gould, 2011. "Quantifying the structure of food demand in China: An econometric approach," Agricultural Economics, International Association of Agricultural Economists, vol. 42, pages 1-18, November.
    6. Denton, Frank T. & Mountain, Dean C., 2011. "Exploring the effects of aggregation error in the estimation of consumer demand elasticities," Economic Modelling, Elsevier, vol. 28(4), pages 1747-1755, July.
    7. Toshinobu Matsuda, 2007. "Linearizing the inverse quadratic almost ideal demand system," Applied Economics, Taylor & Francis Journals, vol. 39(3), pages 381-396.
    8. Frank T. Denton & Dean C. Mountain, 2007. "Exploring the Effects of Aggregation Error in the Estimation of Consumer Demand Elasticities," Social and Economic Dimensions of an Aging Population Research Papers 226, McMaster University.
    9. Hovhannisyan, Vardges & Gould, Brian W., 2012. "Structural Changes in Chinese Food Preferences," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125978, Agricultural and Applied Economics Association.
    10. Barnett, William A. & Erwin Diewert, W. & Zellner, Arnold, 2011. "Introduction to measurement with theory," Journal of Econometrics, Elsevier, vol. 161(1), pages 1-5, March.
    11. Jaya Jumrani & P. S. Birthal, 2017. "Does consumption of tobacco and alcohol affect household food security? Evidence from rural India," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 9(2), pages 255-279, April.
    12. Thomas F. Crossley & Hamish W. Low, 2011. "Is The Elasticity Of Intertemporal Substitution Constant?," Journal of the European Economic Association, European Economic Association, vol. 9(1), pages 87-105, February.
    13. Angela Daley & Thesia I. Garner & Shelley Phipps & Eva Sierminska, 2020. "Differences across Place and Time in Household Expenditure Patterns: Implications for the Estimation of Equivalence Scales," Economic Working Papers 520, Bureau of Labor Statistics.
    14. Unterschultz, James R., 2000. "New Instruments For Co-Ordination And Risk Sharing Within The Canadian Beef Industry," Project Report Series 24046, University of Alberta, Department of Resource Economics and Environmental Sociology.
    15. Hovhannisyan, Vardges & Stiegert, Kyle W. & Bozic, Marin, 2013. "On Endogeneity Of Retail Market Power In An Equilibrium Analysis: A Control Function Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149830, Agricultural and Applied Economics Association.
    16. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    17. Allais, Olivier & Etilé, Fabrice & Lecocq, Sébastien, 2015. "Mandatory labels, taxes and market forces: An empirical evaluation of fat policies," Journal of Health Economics, Elsevier, vol. 43(C), pages 27-44.
    18. Simon Alder & Timo Boppart & Andreas Müller, 2022. "A Theory of Structural Change That Can Fit the Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 160-206, April.
    19. Barnett, William A. & Serletis, Apostolos, 2008. "The Differential Approach to Demand Analysis and the Rotterdam Model," MPRA Paper 12319, University Library of Munich, Germany.
    20. Frederic Vermeulen, 2002. "Collective Household Models: Principles and Main Results," Journal of Economic Surveys, Wiley Blackwell, vol. 16(4), pages 533-564, September.

    More about this item

    Keywords

    Consumer/Household Economics; Demand and Price Analysis; Research Methods/ Statistical Methods;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:aaea11:103736. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.