IDEAS home Printed from https://ideas.repec.org/a/ags/jlaare/31126.html
   My bibliography  Save this article

Aids Versus The Rotterdam Demand System: A Cox Test With Parametric Bootstrap

Author

Listed:
  • Dameus, Alix
  • Richter, Francisca G.-C.
  • Brorsen, B. Wade
  • Sukhdial, Kullapapruk Piewthongngam

Abstract

A Cox test with parametric bootstrap is developed to select between the linearized version of the First-Difference Almost Ideal Demand System (FDAIDS) and the Rotterdam model. A Cox test with parametric bootstrap has been shown to be more powerful than encompassing tests like those used in past research. The bootstrap approach is used with U.S. meat demand (beef, pork, chicken, fish) and compared to results obtained with an encompassing test. The Cox test with parametric bootstrap consistently indicates the Rotterdam model is preferred to the FDAIDS, while the encompassing test sometimes fails to reject FDAIDS.

Suggested Citation

  • Dameus, Alix & Richter, Francisca G.-C. & Brorsen, B. Wade & Sukhdial, Kullapapruk Piewthongngam, 2002. "Aids Versus The Rotterdam Demand System: A Cox Test With Parametric Bootstrap," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 27(2), pages 1-13, December.
    • Handle: RePEc:ags:jlaare:31126
    DOI: 10.22004/ag.econ.31126
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/31126/files/27020335.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.31126?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. M. H. Pesaran, 1974. "On the General Problem of Model Selection," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 41(2), pages 153-171.
    3. Hashem Pesaran, M. & Pesaran, Bahram, 1993. "A simulation approach to the problem of computing Cox's statistic for testing nonnested models," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 377-392.
    4. Terry L. Kastens & Gary W. Brester, 1996. "Model Selection and Forecasting Ability of Theory-Constrained Food Demand Systems," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 301-312.
    5. 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.
    6. Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
    7. Maasoumi, Esfandiar, 2001. "On the relevance of first-order asymptotic theory to economics," Journal of Econometrics, Elsevier, vol. 100(1), pages 83-86, January.
    8. N. Coulibaly & B. Wade Brorsen, 1999. "Monte carlo sampling approach to testing nonnested hypothesis: monte carlo results," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 195-209.
    9. Jeffrey T. LaFrance, 1998. "The Silence Bleating! of the Lambdas: Comment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 221-230.
    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. Taljaard, Pieter R. & van Schalkwyk, Herman D. & Alemu, Zerihun Gudeta, 2006. "Choosing between the AIDS and Rotterdam models: A meat demand analysis case study," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 45(2), pages 1-15, June.
    2. Tonsor, Glynn T. & Kastens, Terry L., 2006. "How Much Do Starting Values Really Matter? An Empirical Comparison of Genetic Algorithm and Traditional Approaches," 2006 Annual meeting, July 23-26, Long Beach, CA 21252, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Shida Rastegari Henneberry & Joao E. Mutondo, 2009. "Agricultural Trade among NAFTA Countries: A Case Study of U.S. Meat Exports," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(3), pages 424-445.
    4. Stavroula Malla & K. K. Klein & Taryn Presseau, 2020. "Have health claims affected demand for fats and meats in Canada?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(3), pages 271-287, September.
    5. 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).
    6. Laura Cornelsen & Mario Mazzocchi & Rosemary Green & Alan D. Dangour & Richard D. Smith, 2016. "Estimating the Relationship between Food Prices and Food Consumption—Methods Matter," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 38(3), pages 546-561.

    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. Dameus, Alix & Brorsen, B. Wade & Sukhdial, Kullapapruk Piewthongngam & Richter, Francisca G.-C., 2001. "Aids Versus Rotterdam: A Cox Nonnested Test With Parametric Bootstrap," 2001 Annual meeting, August 5-8, Chicago, IL 20453, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    3. Kapetanios, G. & Weeks, M., 2003. "Non-nested Models and the likelihood Ratio Statistic: A Comparison of Simulation and Bootstrap-based Tests," Cambridge Working Papers in Economics 0308, Faculty of Economics, University of Cambridge.
    4. McAleer, Michael, 1995. "The significance of testing empirical non-nested models," Journal of Econometrics, Elsevier, vol. 67(1), pages 149-171, May.
    5. Monfardini, Chiara, 2003. "An illustration of Cox's non-nested testing procedure for logit and probit models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 425-444, March.
    6. Park, Seong C. & Brorsen, B. Wade & Stoecker, Arthur L. & Hattey, Jeffory A., 2012. "Forage Response to Swine Effluent: A Cox Nonnested Test of Alternative Functional Forms Using a Fast Double Bootstrap," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(4), pages 593-606, November.
    7. Sun, Yixiao X, 2005. "Estimation and Inference in Panel Structure Models," University of California at San Diego, Economics Working Paper Series qt5tf1231k, Department of Economics, UC San Diego.
    8. van Oest, R.D. & Franses, Ph.H.B.F., 2015. "The Davies Problem: A New Test for Random Slope in the Hierarchical Linear Model," Econometric Institute Research Papers EI 2015-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Ailin Fan & Rui Song & Wenbin Lu, 2017. "Change-Plane Analysis for Subgroup Detection and Sample Size Calculation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 769-778, April.
    10. Maozu Lu & Grayham E. Mizon & Chiara Monfardini, 2008. "Simulation Encompassing: Testing Non‐nested Hypotheses," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 781-806, December.
    11. Berg, Nathan, 2004. "No-decision classification: an alternative to testing for statistical significance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 631-650, November.
    12. Julian Alston & James Chalfant & Nicholas Piggott, 2002. "Estimating and testing the compensated double-log demand model," Applied Economics, Taylor & Francis Journals, vol. 34(9), pages 1177-1186.
    13. Godfrey, Leslie G., 2007. "On the asymptotic validity of a bootstrap method for testing nonnested hypotheses," Economics Letters, Elsevier, vol. 94(3), pages 408-413, March.
    14. Coulibaly, Nouhoun & Brorsen, B. Wade, 1997. "A Monte Carlo Sampling Approach to Testing Separate Families of Hypotheses: Monte Carlo Results," 1997 Annual Meeting, July 13-16, 1997, Reno\ Sparks, Nevada 35879, Western Agricultural Economics Association.
    15. Christophe Bontemps & Grayham E. Mizon, 2008. "Encompassing: Concepts and Implementation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 721-750, December.
    16. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    17. N. Coulibaly & B. Wade Brorsen, 1999. "Monte carlo sampling approach to testing nonnested hypothesis: monte carlo results," Econometric Reviews, Taylor & Francis Journals, vol. 18(2), pages 195-209.
    18. Masahito Kobayashi, 2005. "Testing for Volatility Jumps in the Stochastic Volatility Process," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 12(2), pages 143-157, June.
    19. Kaitibie, Simeon & Nganje, William E. & Brorsen, B. Wade & Epplin, Francis M., 2003. "Optimal Grazing Pressure Under Output Price And Production Uncertainty With Alternative Functional Forms," 2003 Annual meeting, July 27-30, Montreal, Canada 22020, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Godwin Nwaobi, 2001. "A Vector Error Correction And Nonnested Modelling Of Money Demand Function In Nigeria," Econometrics 0111004, University Library of Munich, Germany.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    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:jlaare:31126. 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/waeaaea.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.