IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v38y2004i5p459-475.html
   My bibliography  Save this article

A new approach for travel demand modeling: linking Roy's Identity to discrete choice

Author

Listed:
  • Kockelman, Kara Maria
  • Krishnamurthy, Sriram

Abstract

The variety of choice alternatives in travel contexts has led to significant simplifications of behavior in models of these complex decisions. Typically, several demand submodels are run independently, producing relatively disconnected estimates of trip generation, destination choice, mode, and time of day. This work relies on nested behavioral models for cost minimization and applications of Roy's Identity to the ensuing comprehensive cost values. The end result is a behaviorally grounded model of travel demand across any number of choice dimensions. These are subject to a general budget constraint based on time and money limitations. Unlike existing models, the model produces rigorous welfare measures recognizing all aspects of travel choice. For purposes of illustration, the model was calibrated using Austin, TX travel-diary data and a modified-translog indirect utility specification. Results indicate that Austinites are less flexible about mode choice than destination choice for non-work trips and that the elasticity of trip generation with respect to travel times and costs is very low. In addition, welfare analyses using equivalent variation measures were performed under various network and policy scenarios, including congestion pricing. These strictly accommodate the welfare impacts of network and land use changes on trip-generation and other travel choices; the resulting estimates suggest flexibility in trip-making.

Suggested Citation

  • Kockelman, Kara Maria & Krishnamurthy, Sriram, 2004. "A new approach for travel demand modeling: linking Roy's Identity to discrete choice," Transportation Research Part B: Methodological, Elsevier, vol. 38(5), pages 459-475, June.
  • Handle: RePEc:eee:transb:v:38:y:2004:i:5:p:459-475
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191-2615(03)00076-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kockelman, Kara M., 1998. "A Utility-Theory-Consistent System-of-Demand-Equations Approach to Household Travel Choice," University of California Transportation Center, Working Papers qt3h67j2p2, University of California Transportation Center.
    2. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    3. Hausman, Jerry A. & Leonard, Gregory K. & McFadden, Daniel, 1995. "A utility-consistent, combined discrete choice and count data model Assessing recreational use losses due to natural resource damage," Journal of Public Economics, Elsevier, vol. 56(1), pages 1-30, January.
    4. Small, Kenneth A & Rosen, Harvey S, 1981. "Applied Welfare Economics with Discrete Choice Models," Econometrica, Econometric Society, vol. 49(1), pages 105-130, January.
    5. Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
    6. Pollak, Robert A & Wales, Terence J, 1980. "Comparison of the Quadratic Expenditure System and Translog Demand Systems with Alternative Specifications of Demographic Effects," Econometrica, Econometric Society, vol. 48(3), pages 595-612, April.
    7. Christensen, Laurits R & Jorgenson, Dale W & Lau, Lawrence J, 1975. "Transcendental Logarithmic Utility Functions," American Economic Review, American Economic Association, vol. 65(3), pages 367-383, June.
    8. Kockelman, Kara Maria, 2001. "A model for time- and budget-constrained activity demand analysis," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 255-269, March.
    9. Kockelman, Kara Maria, 1998. "A Utility-Theory-Consistem System-of-Demand-Equations Approach to Household Travel Choice," University of California Transportation Center, Working Papers qt06x0k5r4, University of California Transportation Center.
    10. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    11. Golob, Thomas F. & Beckmann, Martin J. & Zahavi, Yacov, 1981. "A utility-theory travel demand model incorporating travel budgets," Transportation Research Part B: Methodological, Elsevier, vol. 15(6), pages 375-389, December.
    12. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    13. Deaton,Angus & Muellbauer,John, 1980. "Economics and Consumer Behavior," Cambridge Books, Cambridge University Press, number 9780521296762.
    14. Pollak, Robert A & Wales, Terence J, 1978. "Estimation of Complete Demand Systems from Household Budget Data: The Linear and Quadratic Expenditure Systems," American Economic Review, American Economic Association, vol. 68(3), pages 348-359, June.
    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. Chorus, Caspar G., 2012. "Logsums for utility-maximizers and regret-minimizers, and their relation with desirability and satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1003-1012.
    2. Takuya Satomura & Jaehwan Kim & Greg M. Allenby, 2011. "Multiple-Constraint Choice Models with Corner and Interior Solutions," Marketing Science, INFORMS, vol. 30(3), pages 481-490, 05-06.

    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. Kockelman, Kara Maria, 2001. "A model for time- and budget-constrained activity demand analysis," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 255-269, March.
    2. Marsh, Thomas L. & Piggott, Nicholas E., 2013. "Measuring Pre-Commited Quantities Through Consumer Price Formation," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152165, Australian Agricultural and Resource Economics Society.
    3. Sanvi Avouyi-Dovi & Christian Pfister & Franck Sédillot, 2019. "French Households’ Portfolio: The Financial Almost Ideal Demand System Appraisal," Working papers 728, Banque de France.
    4. Chen, Shu-Ling & Chern, Wen S. & Lin, Yi-Ru & Liu, Kang Ernest, 2015. "Effects of food safety and health risk information on demand for food in Taiwan," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205452, Agricultural and Applied Economics Association.
    5. Chern, Wen S. & Lee, Hwang Jaw, 1989. "Nonparametric and Parametric Analyses of Demand for Food at Home and Away from Home," 1989 Annual Meeting, July 30-August 2, Baton Rouge, Louisiana 270706, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Mora Rodriguez, Jhon James, 2013. "Introduccion a la teoría del consumidor [Introduction to Consumer Theory]," MPRA Paper 48129, University Library of Munich, Germany, revised 08 Jul 2013.
    7. Elsner, Karin, 1999. "Analysing Russian Food Expenditure Using Micro-Data," IAMO Discussion Papers 14909, Institute of Agricultural Development in Transition Economies (IAMO).
    8. Simona Bigerna & Carlo Andrea Bollino & Maria Chiara D’Errico, 2020. "A general expenditure system for estimation of consumer demand functions," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 1071-1088, October.
    9. Huang, Min-Hsin & Hahn, David E. & Jones, Eugene, 2004. "Determinants Of Price Elasticities For Store Brands And National Brands Of Cheese," 2004 Annual meeting, August 1-4, Denver, CO 20235, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Ping Wang & Nhuong Tran & Dolapo Enahoro & Chin Yee Chan & Kelvin Mashisia Shikuku & Karl M. Rich & Kendra Byrd & Shakuntala H. Thilsted, 2022. "Spatial and temporal patterns of consumption of animal‐source foods in Tanzania," Agribusiness, John Wiley & Sons, Ltd., vol. 38(2), pages 328-348, April.
    11. Elsner, Karin, 1999. "Analysing Russian food expenditure using micro-data," IAMO Discussion Papers 23, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    12. Larson, Douglas M. & Lew, Daniel K., 2005. "Measuring the utility of ancillary travel: revealed preferences in recreation site demand and trips taken," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 237-255.
    13. Barewal, S. & Goddard, D., 1985. "The Parameters of Consumer Food Demand in Canada," Working Papers 243862, Agriculture and Agri-Food Canada.
    14. Allender, William J. & Richards, Timothy J., 2009. "Measures of Brand Loyalty," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49536, Agricultural and Applied Economics Association.
    15. Thomas, Alastair, 2019. "Who Would Win from a Multi-rate GST in New Zealand: Evidence from a QUAIDS Model," Working Paper Series 20932, Victoria University of Wellington, Chair in Public Finance.
    16. Thomas, Alastair, 2019. "Who Would Win from a Multi-rate GST in New Zealand: Evidence from a QUAIDS Model," Working Paper Series 8127, Victoria University of Wellington, Chair in Public Finance.
    17. Barnett, William A. & Serletis, Apostolos, 2008. "Consumer preferences and demand systems," Journal of Econometrics, Elsevier, vol. 147(2), pages 210-224, December.
    18. 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.
    19. Frank T. Denton & Dean C. Mountain, 2016. "Biases in consumer elasticities based on micro and aggregate data: an integrated framework and empirical evaluation," Empirical Economics, Springer, vol. 50(2), pages 531-560, March.
    20. Paula Carvalho Pereda & Denisard Cneio de Oliveira Alves, 2008. "Demand for Nutrients in Brazil," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211136590, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    More about this item

    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:eee:transb:v:38:y:2004:i:5:p:459-475. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.