IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v18y2011i2p326-335.html
   My bibliography  Save this article

Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice

Author

Listed:
  • Bhatta, Bharat P.
  • Larsen, Odd I.

Abstract

Modeling travel demand is a vital part of transportation planning and management. Level of service (LOS) attributes representing the performance of transportation system and characteristics of travelers including their households are major factors determining the travel demand. Information on actual choice and characteristics of travelers is obtained from a travel survey at an individual level. Since accurate measurement of LOS attributes such as travel time and cost components for different travel modes at an individual level is critical, they are normally obtained from network models. The network-based LOS attributes introduce measurement errors to individual trips thereby causing errors in variables problem in a disaggregate model of travel demand. This paper investigates the possible structure and magnitude of biases introduced to the coefficients of a multinomial logit model of travel mode choice due to random measurement errors in two variables, namely, access/egress time for public transport and walking and cycling distance to work. A model was set up that satisfies the standard assumptions of a multinomial logit model. This model was estimated on a data set from a travel survey on the assumption of correctly measured variables. Subsequently random measurement errors were introduced and the mean values of the parameters from 200 estimations were presented and compared with the original estimates. The key finding in this paper is that errors in variables result in biased parameter estimates of a multinomial logit model and consequently leading to poor policy decisions if the models having biased parameters are applied in policy and planning purposes. In addition, the paper discusses some potential remedial measures and identifies research topics that deserve a detailed investigation to overcome the problem. The paper therefore significantly contributes to bridge the gap between theory and practice in transport.

Suggested Citation

  • Bhatta, Bharat P. & Larsen, Odd I., 2011. "Errors in variables in multinomial choice modeling: A simulation study applied to a multinomial logit model of travel mode choice," Transport Policy, Elsevier, vol. 18(2), pages 326-335, March.
    • Handle: RePEc:eee:trapol:v:18:y:2011:i:2:p:326-335
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967-070X(10)00120-4
    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. McFadden, Daniel L., 1984. "Econometric analysis of qualitative response models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 24, pages 1395-1457, Elsevier.
    2. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    3. Bound, John & Brown, Charles & Mathiowetz, Nancy, 2001. "Measurement error in survey data," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 59, pages 3705-3843, Elsevier.
    4. Hu, Yingyao, 2006. "Bounding parameters in a linear regression model with a mismeasured regressor using additional information," Journal of Econometrics, Elsevier, vol. 133(1), pages 51-70, July.
    5. Kao, Chihwa & Schnell, John F., 1987. "Errors in variables in the multinomial response model," Economics Letters, Elsevier, vol. 25(3), pages 249-254.
    6. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-139, February.
    7. Catalano, Mario & Lo Casto, Barbara & Migliore, Marco, 2008. "Car sharing demand estimation and urban transport demand modelling using stated preference techniques," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 40, pages 33-50.
    8. Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
    9. Brownstone, David, 2001. "Discrete Choice Modeling for Transportation," University of California Transportation Center, Working Papers qt29v7d1pk, University of California Transportation Center.
    10. Li, Tong & Hsiao, Cheng, 2004. "Robust estimation of generalized linear models with measurement errors," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 51-65.
    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. Nirmale, Sangram Krishna & Pinjari, Abdul Rawoof, 2023. "Discrete choice models with multiplicative stochasticity in choice environment variables: Application to accommodating perception errors in driver behaviour models," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 169-193.
    2. F. J. Callado-Munoz & J. Gonzalez-Chapela & N. Utrero-Gonzalez, 2017. "Analysis of Variance in Household Financial Portfolio Choice: Evidence from Spain," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(5), pages 439-459, October.
    3. Peer, Stefanie & Knockaert, Jasper & Koster, Paul & Tseng, Yin-Yen & Verhoef, Erik T., 2013. "Door-to-door travel times in RP departure time choice models: An approximation method using GPS data," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 134-150.
    4. 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.
    5. Stuart Donovan & Thomas de Graaff & Henri L.F. de Groot, 2023. "An inexact science: Accounting for measurement error and downward bias in mode and location choice models," Tinbergen Institute Discussion Papers 23-010/VIII, Tinbergen Institute.
    6. Zhengying Liu & Astrid Kemperman & Harry Timmermans, 2020. "Location Choice in the Context of Older Adults’ Leisure-Time Walking," IJERPH, MDPI, vol. 17(13), pages 1-15, July.
    7. Díaz, Federico & Cantillo, Víctor & Arellana, Julian & Ortúzar, Juan de Dios, 2015. "Accounting for stochastic variables in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 222-237.

    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. Nirmale, Sangram Krishna & Pinjari, Abdul Rawoof, 2023. "Discrete choice models with multiplicative stochasticity in choice environment variables: Application to accommodating perception errors in driver behaviour models," Transportation Research Part B: Methodological, Elsevier, vol. 170(C), pages 169-193.
    2. Fabrice Defever, 2006. "Functional fragmentation and the location of multinational firms in the enlarged Europe," Post-Print halshs-00118808, HAL.
    3. 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.
    4. 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.
    5. Ijeoma P. Edoka, 2017. "Implications of Misclassification Errors in Empirical Studies of Adolescent Smoking Behaviours," Health Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 486-499, April.
    6. Deng, Ping & Hu, Yingyao, 2009. "Bounding the effect of a dichotomous regressor with arbitrary measurement errors," Economics Letters, Elsevier, vol. 105(3), pages 256-260, December.
    7. Molinari, Francesca, 2008. "Partial identification of probability distributions with misclassified data," Journal of Econometrics, Elsevier, vol. 144(1), pages 81-117, May.
    8. 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).
    9. Defever, Fabrice, 2006. "Functional fragmentation and the location of multinational firms in the enlarged Europe," Regional Science and Urban Economics, Elsevier, vol. 36(5), pages 658-677, September.
    10. Richard G. Newell & Juha Siikamäki, 2014. "Nudging Energy Efficiency Behavior: The Role of Information Labels," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 1(4), pages 555-598.
    11. Stephane Hess & Denis Bolduc & John Polak, 2010. "Random covariance heterogeneity in discrete choice models," Transportation, Springer, vol. 37(3), pages 391-411, May.
    12. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Takanori Ida & Toshifumi Kuroda, 2009. "Discrete choice model analysis of mobile telephone service demand in Japan," Empirical Economics, Springer, vol. 36(1), pages 65-80, February.
    14. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Misclassification in binary choice models," Journal of Econometrics, Elsevier, vol. 200(2), pages 295-311.
    15. Marcucci, Edoardo & Gatta, Valerio, 2011. "Regional airport choice: Consumer behaviour and policy implications," Journal of Transport Geography, Elsevier, vol. 19(1), pages 70-84.
    16. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    17. Robert Kaestner, 1995. "The Effects of Cocaine and Marijuana Use on Marriage and Marital Stability," NBER Working Papers 5038, National Bureau of Economic Research, Inc.
    18. John Abowd & Martha Stinson, 2011. "Estimating Measurement Error in SIPP Annual Job Earnings: A Comparison of Census Bureau Survey and SSA Administrative Data," Working Papers 11-20, Center for Economic Studies, U.S. Census Bureau.
    19. Kaspar W thrich, 2013. "Set Identification of Generalized Linear Predictors in the Presence of Non-Classical Measurement Errors," Diskussionsschriften dp1304, Universitaet Bern, Departement Volkswirtschaft.
    20. Anthony Edo & Nicolas Jacquemet & Constantine Yannelis, 2019. "Language skills and homophilous hiring discrimination: Evidence from gender and racially differentiated applications," Review of Economics of the Household, Springer, vol. 17(1), pages 349-376, March.

    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:trapol:v:18:y:2011:i:2:p:326-335. 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/30473/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.