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Non-Linear Mixed Logit

Author

Listed:
  • Steffen Andersen

    (Copenhagen Business School)

  • Glenn W. Harrison

    (Robinson College of Business, Georgia State University)

  • Morten Lau

    (Durham Business School)

  • Elisabet E. Rutstroem

    (Robinson College of Business, Georgia State University)

Abstract

We develop an extension of the familiar linear mixed logit model to allow for the direct estimation of parametric non-linear functions defined over structural parameters. Classic applications include the estimation of coefficients of utility functions to characterize risk attitudes and discounting functions to characterize impatience. There are several unexpected benefits of this extension, apart from the ability to directly estimate structural parameters of theoretical interest.

Suggested Citation

  • Steffen Andersen & Glenn W. Harrison & Morten Lau & Elisabet E. Rutstroem, 2011. "Non-Linear Mixed Logit," Department of Economics Working Papers 2011_04, Durham University, Department of Economics.
    • Handle: RePEc:dur:durham:2011_04
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    File URL: http://dro.dur.ac.uk/10348
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    • Andersen, Steffen & Harrison, Glenn W. & Hole, Arne Risa & Rutström, Elisabet E., 2010. "Non-Linear Mixed Logit," Working Papers 04-2010, Copenhagen Business School, Department of Economics.

    References listed on IDEAS

    as
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    12. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    13. David M. Drukker & Richard Gates, 2006. "Generating Halton sequences using Mata," Stata Journal, StataCorp LP, vol. 6(2), pages 214-228, June.
    14. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, September.
    15. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
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    Cited by:

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    2. Kerri Brick & Martine Visser & Justine Burns, 2012. "Risk Aversion: Experimental Evidence from South African Fishing Communities," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(1), pages 133-152.
    3. 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.
    4. Fossen, Frank M. & Glocker, Daniela, 2017. "Stated and revealed heterogeneous risk preferences in educational choice," European Economic Review, Elsevier, vol. 97(C), pages 1-25.
    5. Day, Brett & Bateman, Ian & Binner, Amy & Ferrini, Silvia & Fezzi, Carlo, 2019. "Structurally-consistent estimation of use and nonuse values for landscape-wide environmental change," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    6. Thomas Meissner & David Albrecht, 2022. "Debt Aversion: Theory and Measurement," Papers 2207.07538, arXiv.org, revised Jul 2022.
    7. Li, Zheng, 2018. "Unobserved and observed heterogeneity in risk attitudes: Implications for valuing travel time savings and travel time variability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 12-18.
    8. Emmanuel Kemel & Muriel Travers, 2016. "Comparing attitudes toward time and toward money in experience-based decisions," Theory and Decision, Springer, vol. 80(1), pages 71-100, January.
    9. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2013. "Discounting Behaviour and the Magnitude Effect: Evidence from a Field Experiment in Denmark," Economica, London School of Economics and Political Science, vol. 80(320), pages 670-697, October.
    10. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2017. "Integrating attribute non-attendance and value learning with risk attitudes and perceptual conditioning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 172-191.
    11. Lejarraga, Tomás & Lucena, Abel & Rubí-Barceló, Antoni, 2020. "Beliefs estimated from choices in Proposer-Responder Games," Journal of Economic Behavior & Organization, Elsevier, vol. 179(C), pages 442-459.
    12. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    13. Anna Conte & Peter G Moffatt & Mary Riddel, 2019. "The Multivariate Random Preference Estimatorfor Switching Multiple Price List Data," University of East Anglia School of Economics Working Paper Series 2019-04, School of Economics, University of East Anglia, Norwich, UK..
    14. Meyer, Andrew G., 2015. "The impacts of elicitation mechanism and reward size on estimated rates of time preference," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 58(C), pages 132-148.
    15. Balbontin, Camila & Hensher, David A. & Collins, Andrew T., 2017. "Do familiarity and awareness influence voting intention: The case of road pricing reform?," Journal of choice modelling, Elsevier, vol. 25(C), pages 11-27.
    16. Glenn Harrison & J. Swarthout, 2014. "Experimental payment protocols and the Bipolar Behaviorist," Theory and Decision, Springer, vol. 77(3), pages 423-438, October.
    17. Aguilar, Francisco X. & Cai, Zhen & Mohebalian, Phillip & Thompson, Wyatt, 2015. "Exploring the drivers' side of the “blend wall”: U.S. consumer preferences for ethanol blend fuels," Energy Economics, Elsevier, vol. 49(C), pages 217-226.
    18. Steffen Andersen & John Fountain & Glenn Harrison & Arne Hole & E. Rutström, 2012. "Inferring beliefs as subjectively imprecise probabilities," Theory and Decision, Springer, vol. 73(1), pages 161-184, July.
    19. Burton, Michael P. & Rigby, Dan, 2012. "The Market for Essays," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152195, Australian Agricultural and Resource Economics Society.
    20. Marasco, A. & Picucci, A. & Romano, A., 2016. "Market share dynamics using Lotka–Volterra models," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 49-62.
    21. Wijayaratna, Kasun P. & Dixit, Vinayak V., 2016. "Impact of information on risk attitudes: Implications on valuation of reliability and information," Journal of choice modelling, Elsevier, vol. 20(C), pages 16-34.

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    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

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