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Non-Linear Mixed Logit and the Characterization of Individual Heterogeneity

Author

Listed:
  • Andersen, Steffen

    (Department of Economics, Copenhagen Business School)

  • Harrison, Glenn W.
  • Hole, Arne Risa
  • Rutström, Elisabet E.

Abstract

Experimental data exhibit considerable individual heterogeneity. We review the econometric methods employed to characterize that heterogeneity. We pay particular attention to the trade-off between collecting and allowing for observable characteristics, such as the familiar demographics, and the use of statistical methods to allow for unobserved individual heterogeneity. We demonstrate that these tools are complementary.

Suggested Citation

  • Andersen, Steffen & Harrison, Glenn W. & Hole, Arne Risa & Rutström, Elisabet E., 2009. "Non-Linear Mixed Logit and the Characterization of Individual Heterogeneity," Working Papers 06-2009, Copenhagen Business School, Department of Economics.
  • Handle: RePEc:hhs:cbsnow:2009_006
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    Citations

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    Cited by:

    1. Antoni Bosch-Domènech & José Montalvo & Rosemarie Nagel & Albert Satorra, 2010. "A finite mixture analysis of beauty-contest data using generalized beta distributions," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 461-475, December.
    2. Zheng Li & David Hensher, 2010. "Prospect Theoretic Contributions in Understanding Traveller Behaviour: A Review and Some Comments," Transport Reviews, Taylor & Francis Journals, vol. 31(1), pages 97-115, May.
    3. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    4. Achtnicht, Martin, 2011. "Do environmental benefits matter? Evidence from a choice experiment among house owners in Germany," Ecological Economics, Elsevier, vol. 70(11), pages 2191-2200, September.
    5. Hensher, David A. & Greene, William H. & Li, Zheng, 2011. "Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 954-972, August.

    More about this item

    Keywords

    econometrics; demography;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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