IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v36y2020ics1755534520300233.html
   My bibliography  Save this article

Individual-specific posterior distributions from Mixed Logit models: Properties, limitations and diagnostic checks

Author

Listed:
  • Sarrias, Mauricio

Abstract

Individual-specific posterior distributions are an attractive tool for disentangling the tastes for each person in the sample. However, there exists some risks and certain limitations regarding their use. This study reviews and summarizes the theoretical literature about the individual-specific posterior distributions derived from the Mixed Logit model, focusing on their properties, limitations and common pitfalls. It also reviews and analyzes the behavior of some diagnostic checks proposed in the literature for the reliability of such estimates in applied works using Monte Carlo experiments. Finally, this article provides reasonable guidelines for the correct use of individual-specific posterior distributions.

Suggested Citation

  • Sarrias, Mauricio, 2020. "Individual-specific posterior distributions from Mixed Logit models: Properties, limitations and diagnostic checks," Journal of choice modelling, Elsevier, vol. 36(C).
    • Handle: RePEc:eee:eejocm:v:36:y:2020:i:c:s1755534520300233
    DOI: 10.1016/j.jocm.2020.100224
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534520300233
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2020.100224?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. Joel Huber and Kenneth Train., 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Economics Working Papers E00-289, University of California at Berkeley.
    2. David A Hensher & William H Greene & John M Rose, 2006. "Deriving Willingness-to-Pay Estimates of Travel-Time Savings from Individual-Based Parameters," Environment and Planning A, , vol. 38(12), pages 2365-2376, December.
    3. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Richter, Laura-Lucia & Pollitt, Michael G., 2018. "Which smart electricity service contracts will consumers accept? The demand for compensation in a platform market," Energy Economics, Elsevier, vol. 72(C), pages 436-450.
    6. Danny Campbell & W George Hutchinson & Riccardo Scarpa, 2009. "Using Choice Experiments to Explore the Spatial Distribution of Willingness to Pay for Rural Landscape Improvements," Environment and Planning A, , vol. 41(1), pages 97-111, January.
    7. Sandorf, Erlend Dancke & Campbell, Danny & Hanley, Nick, 2017. "Disentangling the influence of knowledge on attribute non-attendance," Journal of choice modelling, Elsevier, vol. 24(C), pages 36-50.
    8. David Revelt and Kenneth Train., 2000. "Customer-Specific Taste Parameters and Mixed Logit: Households' Choice of Electricity Supplier," Economics Working Papers E00-274, University of California at Berkeley.
    9. Hess, Stephane, 2007. "Posterior analysis of random taste coefficients in air travel behaviour modelling," Journal of Air Transport Management, Elsevier, vol. 13(4), pages 203-212.
    10. Wiktor Budziński & Danny Campbell & Mikołaj Czajkowski & Urška Demšar & Nick Hanley, 2018. "Using Geographically Weighted Choice Models to Account for the Spatial Heterogeneity of Preferences," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 606-626, September.
    11. Hess, Stephane & Hensher, David A., 2010. "Using conditioning on observed choices to retrieve individual-specific attribute processing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 781-790, July.
    12. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    13. Mauricio Sillano & Juan de Dios Ortúzar, 2005. "Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence," Environment and Planning A, , vol. 37(3), pages 525-550, March.
    14. Andrew Daly & Stephane Hess & Kenneth Train, 2012. "Assuring finite moments for willingness to pay in random coefficient models," Transportation, Springer, vol. 39(1), pages 19-31, January.
    15. Michael Keane & Nada Wasi, 2013. "Comparing Alternative Models Of Heterogeneity In Consumer Choice Behavior," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(6), pages 1018-1045, September.
    16. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
    17. Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.
    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. Xiyuan Ren & Joseph Y. J. Chow, 2023. "Nonparametric estimation of k-modal taste heterogeneity for group level agent-based mixed logit," Papers 2309.13159, arXiv.org.
    2. Daziano, Ricardo & Budziński, Wiktor, 2023. "Evolution of preferences for COVID-19 vaccine throughout the pandemic – The choice experiment approach," Social Science & Medicine, Elsevier, vol. 332(C).
    3. Jiang, Ying & Guo, Zijian & Zhang, Runsen & Zong, Weiyan & Zhang, Junyi, 2023. "How do expected changes in life affect young people's stated ownership of privately-owned autonomous vehicles: A comparative study," Transport Policy, Elsevier, vol. 135(C), pages 71-81.
    4. Valeria M. Toledo‐Gallegos & Jed Long & Danny Campbell & Tobias Börger & Nick Hanley, 2021. "Spatial clustering of willingness to pay for ecosystem services," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 673-697, September.
    5. Ren, Xiyuan & Chow, Joseph Y.J., 2022. "A random-utility-consistent machine learning method to estimate agents’ joint activity scheduling choice from a ubiquitous data set," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 396-418.
    6. Lauren Chenarides & Carola Grebitus & Jayson L Lusk & Iryna Printezis, 2022. "A calibrated choice experiment method," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(5), pages 971-1004.
    7. Ahi, Jülide Ceren & Aanesen, Margrethe & Kipperberg, Gorm, 2023. "Testing the sensitivity of stated environmental preferences to variations in choice architecture," Ecological Economics, Elsevier, vol. 205(C).

    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. Sarrias, Mauricio & Daziano, Ricardo A., 2018. "Individual-specific point and interval conditional estimates of latent class logit parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 50-61.
    2. Lauren Chenarides & Carola Grebitus & Jayson L Lusk & Iryna Printezis, 2022. "A calibrated choice experiment method," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(5), pages 971-1004.
    3. Scaccia, Luisa & Marcucci, Edoardo & Gatta, Valerio, 2023. "Prediction and confidence intervals of willingness-to-pay for mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 54-78.
    4. Abildtrup, Jens & Garcia, Serge & Olsen, Søren Bøye & Stenger, Anne, 2013. "Spatial preference heterogeneity in forest recreation," Ecological Economics, Elsevier, vol. 92(C), pages 67-77.
    5. Wiktor Budziński & Mikołaj Czajkowski, 2021. "Accounting for Spatial Heterogeneity of Preferences in Discrete Choice Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(1), pages 1-24, March.
    6. Shr, Yau-Huo & Ready, Richard C. & Orland, Brian & Echols, Stuart, 2017. "Do Visual Representations Influence Survey Responses? Evidence from a Choice Experiment on Landscape Attributes of Green Infrastructure," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258397, Agricultural and Applied Economics Association.
    7. Richter, Laura-Lucia & Pollitt, Michael G., 2018. "Which smart electricity service contracts will consumers accept? The demand for compensation in a platform market," Energy Economics, Elsevier, vol. 72(C), pages 436-450.
    8. Shr, Yau-Huo (Jimmy) & Ready, Richard & Orland, Brian & Echols, Stuart, 2019. "How Do Visual Representations Influence Survey Responses? Evidence from a Choice Experiment on Landscape Attributes of Green Infrastructure," Ecological Economics, Elsevier, vol. 156(C), pages 375-386.
    9. Schmid, Basil & Molloy, Joseph & Peer, Stefanie & Jokubauskaite, Simona & Aschauer, Florian & Hössinger, Reinhard & Gerike, Regine & Jara-Diaz, Sergio R. & Axhausen, Kay W., 2021. "The value of travel time savings and the value of leisure in Zurich: Estimation, decomposition and policy implications," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 186-215.
    10. Hess, Stephane & Train, Kenneth, 2017. "Correlation and scale in mixed logit models," Journal of choice modelling, Elsevier, vol. 23(C), pages 1-8.
    11. Narine Yegoryan & Daniel Guhl & Friederike Paetz, 2023. "When Zeros Count: Confounding in Preference Heterogeneity and Attribute Non-attendance," Rationality and Competition Discussion Paper Series 482, CRC TRR 190 Rationality and Competition.
    12. Mikołaj Czajkowski & Marek Giergiczny & Jakub Kronenberg & Jeffrey Englin, 2019. "The Individual Travel Cost Method with Consumer-Specific Values of Travel Time Savings," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(3), pages 961-984, November.
    13. Holland, Benedict M. & Johnston, Robert J., 2017. "Optimized quantity-within-distance models of spatial welfare heterogeneity," Journal of Environmental Economics and Management, Elsevier, vol. 85(C), pages 110-129.
    14. Valeria M. Toledo‐Gallegos & Jed Long & Danny Campbell & Tobias Börger & Nick Hanley, 2021. "Spatial clustering of willingness to pay for ecosystem services," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 673-697, September.
    15. Simon Behrendt & Georg Wamser, 2018. "Tax-Response Heterogeneity and the Effects of Double Taxation Treaties on the Location Choices of Multinational Firms," CESifo Working Paper Series 6869, CESifo.
    16. Chen, Xuqi & Shen, Meng & Gao, Zhifeng, 2017. "Impact of Intra-respondent Variations in Attribute Attendance on Consumer Preference in Food Choice," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258509, Agricultural and Applied Economics Association.
    17. Villas-Boas, Sofia B & Taylor, Rebecca & Krovetz, Hannah, 2016. "Willingness to Pay for Low Water Footprint Food Choices During Drought," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9vh3x180, Department of Agricultural & Resource Economics, UC Berkeley.
    18. Szabó, Andrea & Pham, Vinh, 2022. "Net neutrality and consumer demand in the video on-demand market," Information Economics and Policy, Elsevier, vol. 61(C).
    19. Ricardo A. Daziano, 2022. "A choice experiment assessment of stated early response to COVID-19 vaccines in the USA," Health Economics Review, Springer, vol. 12(1), pages 1-16, December.
    20. Broberg, Thomas & Daniel, Aemiro Melkamu & Persson, Lars, 2021. "Household preferences for load restrictions: Is there an effect of pro-environmental framing?," Energy Economics, Elsevier, vol. 97(C).

    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:eejocm:v:36:y:2020:i:c:s1755534520300233. 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.journals.elsevier.com/journal-of-choice-modelling .

    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.