IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v8y2008i2p109-124.html
   My bibliography  Save this article

Empirical Identification in the Mixed Logit Model: Analysing the Effect of Data Richness

Author

Listed:
  • Elisabetta Cherchi
  • Juan Dios Ortúzar

Abstract

No abstract is available for this item.

Suggested Citation

  • Elisabetta Cherchi & Juan Dios Ortúzar, 2008. "Empirical Identification in the Mixed Logit Model: Analysing the Effect of Data Richness," Networks and Spatial Economics, Springer, vol. 8(2), pages 109-124, September.
    • Handle: RePEc:kap:netspa:v:8:y:2008:i:2:p:109-124
    DOI: 10.1007/s11067-007-9045-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11067-007-9045-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-007-9045-4?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
    ---><---

    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. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    2. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    3. Williams, H. C. W. L. & Ortuzar, J. D., 1982. "Behavioural theories of dispersion and the mis-specification of travel demand models," Transportation Research Part B: Methodological, Elsevier, vol. 16(3), pages 167-219, June.
    4. Swait, Joffre & Bernardino, Adriana, 2000. "Distinguishing taste variation from error structure in discrete choice data," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 1-15, January.
    5. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    6. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    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. Zhifeng Gao & Ted C. Schroeder, 2009. "Consumer responses to new food quality information: are some consumers more sensitive than others?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 339-346, May.
    2. 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.
    3. Cherchi, Elisabetta & Cirillo, Cinzia & Ortúzar, Juan de Dios, 2017. "Modelling correlation patterns in mode choice models estimated on multiday travel data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 146-153.
    4. Elisabetta Cherchi & Juan de Dios Ortúzar, 2011. "On the Use of Mixed RP/SP Models in Prediction: Accounting for Systematic and Random Taste Heterogeneity," Transportation Science, INFORMS, vol. 45(1), pages 98-108, February.
    5. Olivier Allais; & Fabrice Etile; & Sebastien Lecocq, 2012. "Mandatory labelling, nutritional taxes and market forces: An empirical evaluation of fat policies in the French fromage blanc and yogurt market," Health, Econometrics and Data Group (HEDG) Working Papers 12/14, HEDG, c/o Department of Economics, University of York.
    6. Xuemei Fu & Zhicai Juan, 2017. "Estimation of multinomial probit-kernel integrated choice and latent variable model: comparison on one sequential and two simultaneous approaches," Transportation, Springer, vol. 44(1), pages 91-116, January.
    7. María Yáñez & Patricio Mansilla & Juan de Ortúzar, 2010. "The Santiago Panel: measuring the effects of implementing Transantiago," Transportation, Springer, vol. 37(1), pages 125-149, January.
    8. Gonzalez-Valdes, Felipe & Heydecker, Benjamin G. & Ortúzar, Juan de Dios, 2022. "Quantifying behavioural difference in latent class models to assess empirical identifiability: Analytical development and application to multiple heuristics," Journal of choice modelling, Elsevier, vol. 43(C).
    9. Raveau, Sebastián & Yáñez, María Francisca & Ortúzar, Juan de Dios, 2012. "Practical and empirical identifiability of hybrid discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1374-1383.
    10. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.
    11. Wang, Ning & Tang, Linhao & Pan, Huizhong, 2017. "Effectiveness of policy incentives on electric vehicle acceptance in China: A discrete choice analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 210-218.

    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. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    2. Stephane Hess & John Rose, 2012. "Can scale and coefficient heterogeneity be separated in random coefficients models?," Transportation, Springer, vol. 39(6), pages 1225-1239, November.
    3. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    4. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    5. Hossan, Md Sakoat & Asgari, Hamidreza & Jin, Xia, 2016. "Investigating preference heterogeneity in Value of Time (VOT) and Value of Reliability (VOR) estimation for managed lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 638-649.
    6. Deka, Devajyoti & Carnegie, Jon, 2021. "Predicting transit mode choice of New Jersey workers commuting to New York City from a stated preference survey," Journal of Transport Geography, Elsevier, vol. 91(C).
    7. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    8. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    9. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    10. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
    11. De Ayala Bilbao, Amaya & Hoyos Ramos, David & Mariel Chladkova, Petr, 2012. "Landscape valuation through discrete choice experiments: Current practice and future research reflections," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    12. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
    13. Jasper Willigers & Han Floor & Bert Van Wee, 2005. "High-speed railÂ’s impact on the location of office employment within the Dutch Randstad area," ERSA conference papers ersa05p308, European Regional Science Association.
    14. Tran, Martino, 2012. "Technology-behavioural modelling of energy innovation diffusion in the UK," Applied Energy, Elsevier, vol. 95(C), pages 1-11.
    15. Danielis, Romeo & Rotaris, Lucia & Giansoldati, Marco & Scorrano, Mariangela, 2020. "Drivers’ preferences for electric cars in Italy. Evidence from a country with limited but growing electric car uptake," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 79-94.
    16. Imran Khan & Hongdou Lei & Gaffar Ali & Shahid Ali & Minjuan Zhao, 2019. "Public Attitudes, Preferences and Willingness to Pay for River Ecosystem Services," IJERPH, MDPI, vol. 16(19), pages 1-17, October.
    17. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Bliemer, Michiel C.J. & Rose, John M., 2011. "Experimental design influences on stated choice outputs: An empirical study in air travel choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 63-79, January.
    19. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.

    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:kap:netspa:v:8:y:2008:i:2:p:109-124. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.