IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v46y2019i4d10.1007_s11116-017-9847-2.html
   My bibliography  Save this article

Misclassification in travel surveys and implications to choice modeling: application to household auto ownership decisions

Author

Listed:
  • Rajesh Paleti

    (Old Dominion University)

  • Lacramioara Balan

    (Old Dominion University)

Abstract

Travel surveys that elicit responses to questions regarding daily activity and travel choices form the basis for most of the transportation planning and policy analysis. The response variables collected in these surveys are prone to errors leading to mismeasurement or misclassification. Standard modeling methods that ignore these errors while modeling travel choices can lead to biased parameter estimates. In this study, methods available in the econometrics literature were used to quantify and assess the impact of misclassification errors in auto ownership choice data. The results uncovered significant misclassification rates ranging from 1 to 40% for different auto ownership alternatives. Also, the results from latent class models provide evidence for variation in misclassification probabilities across different population segments. Models that ignore misclassification were not only found to have lower statistical fit but also significantly different elasticity effects for choice alternatives with high misclassification probabilities. The methods developed in this study can be extended to analyze misclassification in several response variables (e.g., mode choice, activity purpose, trip/tour frequency, and mileage) that constitute the core of advanced travel demand models including tour and activity-based models.

Suggested Citation

  • Rajesh Paleti & Lacramioara Balan, 2019. "Misclassification in travel surveys and implications to choice modeling: application to household auto ownership decisions," Transportation, Springer, vol. 46(4), pages 1467-1485, August.
    • Handle: RePEc:kap:transp:v:46:y:2019:i:4:d:10.1007_s11116-017-9847-2
    DOI: 10.1007/s11116-017-9847-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-017-9847-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-017-9847-2?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. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    2. Patrick Bonnel & Michel Le Nir, 1998. "The quality of survey data: Telephone versus face-to-face interviews," Post-Print halshs-00140887, HAL.
    3. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    4. Erik Hurst & Geng Li & Benjamin Pugsley, 2014. "Are Household Surveys Like Tax Forms? Evidence from Income Underreporting of the Self-Employed," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 19-33, March.
    5. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    6. McFadden, Daniel, 1989. "A Method of Simulated Moments for Estimation of Discrete Response Models without Numerical Integration," Econometrica, Econometric Society, vol. 57(5), pages 995-1026, September.
    7. Peter Stopher & Camden FitzGerald & Min Xu, 2007. "Assessing the accuracy of the Sydney Household Travel Survey with GPS," Transportation, Springer, vol. 34(6), pages 723-741, November.
    8. repec:adr:anecst:y:1999:i:55-56:p:09 is not listed on IDEAS
    9. Sabreena Anowar & Shamsunnahar Yasmin & Naveen Eluru & Luis Miranda-Moreno, 2014. "Analyzing car ownership in Quebec City: a comparison of traditional and latent class ordered and unordered models," Transportation, Springer, vol. 41(5), pages 1013-1039, September.
    10. Ramalho, Esmeralda A., 2002. "Regression models for choice-based samples with misclassification in the response variable," Journal of Econometrics, Elsevier, vol. 106(1), pages 171-201, January.
    11. Brownstone, David & Bunch, David S & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Department of Economics, Working Paper Series qt45f996hh, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    12. William H. Greene & David A. Hensher, 2013. "Revealing additional dimensions of preference heterogeneity in a latent class mixed multinomial logit model," Applied Economics, Taylor & Francis Journals, vol. 45(14), pages 1897-1902, May.
    13. Dustmann C. & Van Soest A., 2004. "An Analysis of Speaking Fluency of Immigrants Using Ordered Response Models With Classification Errors," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 312-321, July.
    14. Paleti, Rajesh, 2015. "Implicit choice set generation in discrete choice models: Application to household auto ownership decisions," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 132-149.
    15. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    16. Bhat, Chandra R., 2003. "Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences," Transportation Research Part B: Methodological, Elsevier, vol. 37(9), pages 837-855, November.
    17. Fred Mannering & Clifford Winston, 1985. "A Dynamic Empirical Analysis of Household Vehicle Ownership and Utilization," RAND Journal of Economics, The RAND Corporation, vol. 16(2), pages 215-236, Summer.
    18. Bhat, Chandra R. & Pulugurta, Vamsi, 1998. "A comparison of two alternative behavioral choice mechanisms for household auto ownership decisions," Transportation Research Part B: Methodological, Elsevier, vol. 32(1), pages 61-75, January.
    19. Kenneth E. Train & Clifford Winston, 2007. "Vehicle Choice Behavior And The Declining Market Share Of U.S. Automakers," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1469-1496, November.
    20. Paul Sullivan, 2009. "Estimation of an Occupational Choice Model when Occupations are Misclassified," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
    21. 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.
    22. Chandra R. Bhat, 1997. "An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel," Transportation Science, INFORMS, vol. 31(1), pages 34-48, February.
    23. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    24. Jason Abrevaya & Jerry A. Hausman, 1999. "Semiparametric Estimation with Mismeasured Dependent Variables: An Application to Duration Models for Unemployment Spells," Annals of Economics and Statistics, GENES, issue 55-56, pages 243-275.
    25. Xiong, Yingge & Mannering, Fred L., 2013. "The heterogeneous effects of guardian supervision on adolescent driver-injury severities: A finite-mixture random-parameters approach," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 39-54.
    26. Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
    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. Downey, Lucy & Fonzone, Achille & Fountas, Grigorios & Semple, Torran, 2022. "The impact of COVID-19 on future public transport use in Scotland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 338-352.

    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. Bhat, Chandra R. & Sen, Sudeshna & Eluru, Naveen, 2009. "The impact of demographics, built environment attributes, vehicle characteristics, and gasoline prices on household vehicle holdings and use," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 1-18, January.
    2. Baltas, George & Saridakis, Charalampos, 2013. "An empirical investigation of the impact of behavioural and psychographic consumer characteristics on car preferences: An integrated model of car type choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 92-110.
    3. Stephane Hess, 2014. "Latent class structures: taste heterogeneity and beyond," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 14, pages 311-330, Edward Elgar Publishing.
    4. Cinzia Cirillo & Renting Xu & Fabian Bastin, 2016. "A Dynamic Formulation for Car Ownership Modeling," Transportation Science, INFORMS, vol. 50(1), pages 322-335, February.
    5. 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.
    6. Xiong, Yingge & Mannering, Fred L., 2013. "The heterogeneous effects of guardian supervision on adolescent driver-injury severities: A finite-mixture random-parameters approach," Transportation Research Part B: Methodological, Elsevier, vol. 49(C), pages 39-54.
    7. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    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. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    10. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    11. Nie, Yu (Marco) & Ghamami, Mehrnaz & Zockaie, Ali & Xiao, Feng, 2016. "Optimization of incentive polices for plug-in electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 103-123.
    12. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    13. Hackbarth, André & Madlener, Reinhard, 2016. "Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 89-111.
    14. Daina, Nicolò & Sivakumar, Aruna & Polak, John W., 2017. "Modelling electric vehicles use: a survey on the methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 447-460.
    15. Wang, Chen & Sun, Jiayi & Russell, Roddy & Daziano, Ricardo A., 2018. "Analyzing willingness to improve the resilience of New York City's transportation system," Transport Policy, Elsevier, vol. 69(C), pages 10-19.
    16. Yang, Chih-Wen & Sung, Yen-Ching, 2010. "Constructing a mixed-logit model with market positioning to analyze the effects of new mode introduction," Journal of Transport Geography, Elsevier, vol. 18(1), pages 175-182.
    17. Kim, Sung Hoo & Mokhtarian, Patricia L., 2018. "Taste heterogeneity as an alternative form of endogeneity bias: Investigating the attitude-moderated effects of built environment and socio-demographics on vehicle ownership using latent class modelin," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 130-150.
    18. Sanjana Hossain & Md. Sami Hasnine & Khandker Nurul Habib, 2021. "A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 48(3), pages 1217-1239, June.
    19. Rico Krueger & Akshay Vij & Taha H. Rashidi, 2018. "A Dirichlet Process Mixture Model of Discrete Choice," Papers 1801.06296, arXiv.org.
    20. Ardeshiri, Ali & Rashidi, Taha Hossein, 2020. "Willingness to pay for fast charging station for electric vehicles with limited market penetration making," Energy Policy, Elsevier, vol. 147(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:kap:transp:v:46:y:2019:i:4:d:10.1007_s11116-017-9847-2. 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.