IDEAS home Printed from https://ideas.repec.org/p/hhs/cbsnow/2010_004.html
   My bibliography  Save this paper

Non-Linear Mixed Logit

Author

Listed:
  • Andersen, Steffen

    (Department of Economics, Copenhagen Business School)

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

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. A classic application is the estimation of coefficients of utility functions to characterize risk attitudes. There are several unexpected benefits of this extension, apart from the ability to directly estimate structural parameters of theoretical interest.

Suggested Citation

  • 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.
  • Handle: RePEc:hhs:cbsnow:2010_004
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10398/8171
    File Function: Full text
    Download Restriction: Full text not avaiable
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Matzkin, Rosa L, 1991. "Semiparametric Estimation of Monotone and Concave Utility Functions for Polychotomous Choice Models," Econometrica, Econometric Society, vol. 59(5), pages 1315-1327, September.
    2. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    3. Chen, Heng Z. & Randall, Alan, 1997. "Semi-nonparametric estimation of binary response models with an application to natural resource valuation," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 323-340.
    4. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    5. White, Halbert, 1980. "Using Least Squares to Approximate Unknown Regression Functions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 149-170, February.
    6. Matzkin, Rosa L, 1992. "Nonparametric and Distribution-Free Estimation of the Binary Threshold Crossing and the Binary Choice Models," Econometrica, Econometric Society, vol. 60(2), pages 239-270, March.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, November.
    8. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    9. Binswanger, Hans P, 1981. "Attitudes toward Risk: Theoretical Implications of an Experiment in Rural India," Economic Journal, Royal Economic Society, vol. 91(364), pages 867-890, December.
    10. David M. Drukker & Richard Gates, 2006. "Generating Halton sequences using Mata," Stata Journal, StataCorp LP, vol. 6(2), pages 214-228, June.
    11. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, November.
    12. 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.
    13. Joseph A. Herriges & Daniel J. Phaneuf, 2002. "Inducing Patterns of Correlation and Substitution in Repeated Logit Models of Recreation Demand," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(4), pages 1076-1090.
    14. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    15. Gallant, A. Ronald, 1981. "On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form," Journal of Econometrics, Elsevier, vol. 15(2), pages 211-245, February.
    16. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, November.
    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. Abi Adams & Laurens Cherchye & Bram De Rock & Ewout Verriest, 2014. "Consume Now or Later? Time Inconsistency, Collective Choice, and Revealed Preference," American Economic Review, American Economic Association, vol. 104(12), pages 4147-4183, December.
    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.

    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. 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.
    2. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten Igel & Rutström, Elisabet E., 2010. "Behavioral econometrics for psychologists," Journal of Economic Psychology, Elsevier, vol. 31(4), pages 553-576, August.
    3. Yuanyuan Gu & Arne Risa Hole & Stephanie Knox, 2013. "Fitting the generalized multinomial logit model in Stata," Stata Journal, StataCorp LP, vol. 13(2), pages 382-397, June.
    4. Daniel J. Henderson & Christopher F. Parmeter, 2009. "Imposing economic constraints in nonparametric regression: survey, implementation, and extension," Advances in Econometrics, in: Nonparametric Econometric Methods, pages 433-469, Emerald Group Publishing Limited.
    5. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2005. "Bayesian Analysis of Consumer Choices with Taste, Context, Reference Point and Individual Scale Effects," 2005 Annual meeting, July 24-27, Providence, RI 19296, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Levon Barseghyan & Francesca Molinari & Ted O'Donoghue & Joshua C. Teitelbaum, 2013. "The Nature of Risk Preferences: Evidence from Insurance Choices," American Economic Review, American Economic Association, vol. 103(6), pages 2499-2529, October.
    7. Marco A. Palma & Dmitry V. Vedenov & David Bessler, 2020. "The order of variables, simulation noise, and accuracy of mixed logit estimates," Empirical Economics, Springer, vol. 58(5), pages 2049-2083, May.
    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. Ajayi, V. & Reiner, D., 2020. "Consumer Willingness to Pay for Reducing the Environmental Footprint of Green Plastics," Cambridge Working Papers in Economics 20110, Faculty of Economics, University of Cambridge.
    10. Probst, Lorenz & Houedjofonon, Elysée & Ayerakwa, Hayford Mensah & Haas, Rainer, 2012. "Will they buy it? The potential for marketing organic vegetables in the food vending sector to strengthen vegetable safety: A choice experiment study in three West African cities," Food Policy, Elsevier, vol. 37(3), pages 296-308.
    11. Ryan Webb, 2019. "The (Neural) Dynamics of Stochastic Choice," Management Science, INFORMS, vol. 65(1), pages 230-255, January.
    12. Phaneuf, Daniel J. & Smith, V. Kerry, 2006. "Recreation Demand Models," Handbook of Environmental Economics, in: K. G. Mäler & J. R. Vincent (ed.), Handbook of Environmental Economics, edition 1, volume 2, chapter 15, pages 671-761, Elsevier.
    13. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    14. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    15. Kesternich, Iris & Heiss, Florian & McFadden, Daniel & Winter, Joachim, 2013. "Suit the action to the word, the word to the action: Hypothetical choices and real decisions in Medicare Part D," Journal of Health Economics, Elsevier, vol. 32(6), pages 1313-1324.
    16. Chetan Dave & Catherine Eckel & Cathleen Johnson & Christian Rojas, 2010. "Eliciting risk preferences: When is simple better?," Journal of Risk and Uncertainty, Springer, vol. 41(3), pages 219-243, December.
    17. Arne Hole & Julie Kolstad, 2012. "Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment," Empirical Economics, Springer, vol. 42(2), pages 445-469, April.
    18. Drichoutis, Andreas & Lusk, Jayson, 2012. "Risk preference elicitation without the confounding effect of probability weighting," MPRA Paper 37762, University Library of Munich, Germany.
    19. Yan, Zhen & Zhou, Jie-hong, 2015. "Measuring consumer heterogeneous preferences for pork traits under media reports: choice experiment in sixteen traceability pilot cities, China," 2015 Conference, August 9-14, 2015, Milan, Italy 212609, International Association of Agricultural Economists.
    20. Jose Apesteguia & Miguel Angel Ballester, 2014. "Discrete Choice Estimation of Risk Aversion," Working Papers 788, Barcelona School of Economics.

    More about this item

    Keywords

    utility functions; risk attitudes; utility theory;
    All these keywords.

    JEL classification:

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

    Statistics

    Access and download statistics

    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:hhs:cbsnow:2010_004. 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: CBS Library Research Registration Team (email available below). General contact details of provider: https://edirc.repec.org/data/incbsdk.html .

    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.