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Modelling non-ignorable attrition and measurement error in panel surveys: an application to travel demand modeling

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  • Brownstone, David
  • Golob, Thomas F.
  • Kazimi, Camilla

Abstract

Modern panel surveys frequently suffer from high and likely non-ignorable attrition, and transportation surveys suffer from poor travel time estimates. This paper examines new methods for adjusting forecasts and model estimates to account for these problems. The methods we describe are illustrated using a new panel survey of 1500 commuters in San Diego, California. These data are being collected to evaluate a federally-funded "Congestion Pricing" experiment investigating the impacts of allowing solo drivers to pay use freeway carpool lanes. The panel survey, begun in Fall 1997, collects data on travel behavior and attitudes at six-month intervals through telephone interviews. The panel sample is refreshed with new respondents at each wave to counteract the attrition between waves. Both the original and refreshment samples are stratified on commuters' mode choices (solo drive in free lanes, pay to solo drive in the carpool lanes, or carpool for free in carpool lanes) to insure sufficient sample size for estimating our models.

Suggested Citation

  • Brownstone, David & Golob, Thomas F. & Kazimi, Camilla, 2002. "Modelling non-ignorable attrition and measurement error in panel surveys: an application to travel demand modeling," University of California Transportation Center, Working Papers qt262891mq, University of California Transportation Center.
    • Handle: RePEc:cdl:uctcwp:qt262891mq
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    References listed on IDEAS

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    1. Imbens, Guido W, 1992. "An Efficient Method of Moments Estimator for Discrete Choice Models with Choice-Based Sampling," Econometrica, Econometric Society, vol. 60(5), pages 1187-1214, September.
    2. Calfee, John & Winston, Clifford, 1998. "The value of automobile travel time: implications for congestion policy," Journal of Public Economics, Elsevier, vol. 69(1), pages 83-102, July.
    3. Imbens, Guido W, 1992. "An Efficient Method of Moments Estimator for Discrete Choice Models with Choice-Based Sampling," Econometrica, Econometric Society, vol. 60(5), pages 1187-1214, September.
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    Citations

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    Cited by:

    1. Brownstone, David & Steimetz, Seiji S. C., 2004. "Estimating Commuters’ “Value of Time” with Noisy Data: a Multiple Imputation Approach," University of California Transportation Center, Working Papers qt6s78c7rt, University of California Transportation Center.
    2. Steimetz, Seiji S.C. & Brownstone, David, 2004. "Estimating Commuters’ “Value of Time” with Noisy Data: a Multiple Imputation Approach," University of California Transportation Center, Working Papers qt52g9r2sd, University of California Transportation Center.
    3. Steimetz, Seiji S.C. & Brownstone, David, 2005. "Estimating commuters' "value of time" with noisy data: a multiple imputation approach," Transportation Research Part B: Methodological, Elsevier, vol. 39(10), pages 865-889, December.
    4. Golob, Thomas F., 1999. "Joint Models of Attitudes and Behavior in Evaluation of the San Diego I-15 Congestion Pricing Project," University of California Transportation Center, Working Papers qt0zs0z136, University of California Transportation Center.
    5. Small, Kenneth A. & Yan, Jia, 2001. "The Value of "Value Pricing" of Roads: Second-Best Pricing and Product Differentiation," Journal of Urban Economics, Elsevier, vol. 49(2), pages 310-336, March.
    6. Steimetz, Siji S.C. & Brownstone, David, 2004. "Estimating Commuters' "Value of Time" and Noisy Data: a Multiple Imputation Approach," University of California Transportation Center, Working Papers qt4qh7m2d0, University of California Transportation Center.
    7. Brownstone, David, 2001. "Discrete Choice Modeling for Transportation," University of California Transportation Center, Working Papers qt29v7d1pk, University of California Transportation Center.
    8. Golob, Thomas F., 2001. "Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(6), pages 495-514, July.
    9. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
    10. Shi, Miaoying & Yin, Runsheng & Lv, Hongdi, 2017. "An empirical analysis of the driving forces of forest cover change in northeast China," Forest Policy and Economics, Elsevier, vol. 78(C), pages 78-87.
    11. Golob, Thomas F., 1999. "Joint Models of Attitudes and Behavior in Evaluation of the San Diego I-15 Congestion Pricing Project," University of California Transportation Center, Working Papers qt16q7w28k, University of California Transportation Center.

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