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Aggregation biases in discrete choice models

Author

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  • Wong, Timothy
  • Brownstone, David
  • Bunch, David S.

Abstract

This paper examines the common practice of aggregating choice alternatives within discrete choice models. We carry out a Monte Carlo study based on realistic vehicle choice data for sample sizes ranging from 500–10,000 individuals. We consider methods for aggregation proposed by McFadden (1978) and Brownstone and Li (2017) as well as the more commonly used methods of choosing a representative disaggregate alternative or averaging the attributes across disaggregate alternatives. The results show that only the “broad choice” aggregation method proposed by Brownstone and Li provides unbiased parameter estimates and confidence bands. Finally, we apply these aggregation methods to study households’ choices of new 2008 model vehicles from the National Household Travel Survey (NHTS) where 1120 unique vehicles are aggregated into 235 make/model classes. Consistent with our Monte Carlo results we find large differences between the resulting estimates across different aggregation methods.

Suggested Citation

  • Wong, Timothy & Brownstone, David & Bunch, David S., 2019. "Aggregation biases in discrete choice models," Journal of choice modelling, Elsevier, vol. 31(C), pages 210-221.
    • Handle: RePEc:eee:eejocm:v:31:y:2019:i:c:p:210-221
    DOI: 10.1016/j.jocm.2018.02.001
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    References listed on IDEAS

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    1. Antonio M. Bento & Lawrence H. Goulder & Mark R. Jacobsen & Roger H. von Haefen, 2009. "Distributional and Efficiency Impacts of Increased US Gasoline Taxes," American Economic Review, American Economic Association, vol. 99(3), pages 667-699, June.
    2. 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.
    3. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
    4. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    5. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
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    Cited by:

    1. Lee, Ungki & Kang, Namwoo & Lee, Ikjin, 2020. "Choice data generation using usage scenarios and discounted cash flow analysis," Journal of choice modelling, Elsevier, vol. 37(C).
    2. Brownstone, David & Li, Phillip, 2018. "A model for broad choice data," Journal of choice modelling, Elsevier, vol. 27(C), pages 19-36.
    3. Shiva Habibi & Emma Frejinger & Marcus Sundberg, 2019. "An empirical study on aggregation of alternatives and its influence on prediction in car type choice models," Transportation, Springer, vol. 46(3), pages 563-582, June.
    4. O. Lunyakov V. & N. Lunyakova A. & О. Луняков В. & Н. Лунякова А., 2018. "Развитие каналов кредитования в условиях перехода к цифровой экономике: моделирование спроса // The Development of Credit Channels in the transition to the Digital Economy: Demand Modelling," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(5), pages 76-89.

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    More about this item

    Keywords

    Discrete choice; Aggregation; Household vehicle demand;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment

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