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A Bayesian mixed logit-probit model for multinomial choice

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Cited by:

  1. Vij, Akshay & Krueger, Rico, 2017. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 76-101.
  2. Schröder, Nadine & Hruschka, Harald, 2016. "Investigating the effects of mailing variables and endogeneity on mailing decisions," European Journal of Operational Research, Elsevier, vol. 250(2), pages 579-589.
  3. Wan, Alan T.K. & Zhang, Xinyu & Wang, Shouyang, 2014. "Frequentist model averaging for multinomial and ordered logit models," International Journal of Forecasting, Elsevier, vol. 30(1), pages 118-128.
  4. Worawan Chandoevwit & Nada Wasi, 2019. "Estimating Demand for Long-term Care Insurance in Thailand: Evidence from a Discrete Choice Experiment," PIER Discussion Papers 106, Puey Ungphakorn Institute for Economic Research.
  5. Martin O'Connell & Pierre Dubois & Rachel Griffith, 2022. "The Use of Scanner Data for Economics Research," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 723-745, August.
  6. Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2019. "Nonparametric estimation of the random coefficients model: An elastic net approach," DICE Discussion Papers 326, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
  7. Pierre Dubois & Rachel Griffith & Martin O'Connell, 2020. "How Well Targeted Are Soda Taxes?," American Economic Review, American Economic Association, vol. 110(11), pages 3661-3704, November.
  8. Steven T. Berry & Philip A. Haile, 2020. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," NBER Working Papers 27704, National Bureau of Economic Research, Inc.
  9. Mark J. Jensen & John M. Maheu, 2018. "Risk, Return and Volatility Feedback: A Bayesian Nonparametric Analysis," JRFM, MDPI, vol. 11(3), pages 1-29, September.
  10. E. Weyl & Michal Fabinger, 2015. "A Tractable Approach to Pass-Through Patterns," 2015 Meeting Papers 747, Society for Economic Dynamics.
  11. Jin, Xin & Maheu, John M., 2016. "Bayesian semiparametric modeling of realized covariance matrices," Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
  12. Akshay Vij & Rico Krueger, 2018. "Random taste heterogeneity in discrete choice models: Flexible nonparametric finite mixture distributions," Papers 1802.02299, arXiv.org.
  13. Bansal, Prateek & Daziano, Ricardo A. & Achtnicht, Martin, 2018. "Comparison of parametric and semiparametric representations of unobserved preference heterogeneity in logit models," Journal of choice modelling, Elsevier, vol. 27(C), pages 97-113.
  14. Bel, K. & Paap, R., 2014. "A Multivariate Model for Multinomial Choices," Econometric Institute Research Papers EI 2014-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  15. Patricia Apps & Jan Kabátek & Ray Rees & Arthur Soest, 2016. "Labor supply heterogeneity and demand for child care of mothers with young children," Empirical Economics, Springer, vol. 51(4), pages 1641-1677, December.
  16. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," Cowles Foundation Discussion Papers 2301, Cowles Foundation for Research in Economics, Yale University.
  17. Michael P. Keane, 2013. "Panel data discrete choice models of consumer demand," Economics Papers 2013-W08, Economics Group, Nuffield College, University of Oxford.
  18. Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
  19. Chernozhukov, Victor & Fernández-Val, Iván & Newey, Whitney K., 2019. "Nonseparable multinomial choice models in cross-section and panel data," Journal of Econometrics, Elsevier, vol. 211(1), pages 104-116.
  20. Yang Li & Asim Ansari, 2014. "A Bayesian Semiparametric Approach for Endogeneity and Heterogeneity in Choice Models," Management Science, INFORMS, vol. 60(5), pages 1161-1179, May.
  21. Kabátek, Jan, 2015. "Essays on public policy and household decision making," Other publications TiSEM 8cdb178e-ad98-42e5-a7e1-b, Tilburg University, School of Economics and Management.
  22. Narine Yegoryan & Daniel Guhl & Friederike Paetz, 2023. "When Zeros Count: Confounding in Preference Heterogeneity and Attribute Non-attendance," Rationality and Competition Discussion Paper Series 482, CRC TRR 190 Rationality and Competition.
  23. Didier Nibbering, 2019. "A High-dimensional Multinomial Choice Model," Monash Econometrics and Business Statistics Working Papers 19/19, Monash University, Department of Econometrics and Business Statistics.
  24. Bazzani, Claudia & Palma, Marco A. & Nayga, Rodolfo M., Jr., 2018. "On the use of flexible mixing distributions in WTP space: an induced value choice experiment," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(2), April.
  25. Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
  26. Jerry Hausman & Haoyang Liu & Ye Luo & Christopher Palmer, 2021. "Errors in the Dependent Variable of Quantile Regression Models," Econometrica, Econometric Society, vol. 89(2), pages 849-873, March.
  27. Cohen, Michael, 2010. "A Structured Covariance Probit Demand Model," Research Reports 149970, University of Connecticut, Food Marketing Policy Center.
  28. Igor Prünster & Matteo Ruggiero, 2011. "A Bayesian nonparametric approach to modeling market share dynamics," Carlo Alberto Notebooks 217, Collegio Carlo Alberto.
  29. Keane, Michael P. & Wasi, Nada, 2016. "How to model consumer heterogeneity? Lessons from three case studies on SP and RP data," Research in Economics, Elsevier, vol. 70(2), pages 197-231.
  30. Balcombe, Kelvin & Fraser, Iain & Williams, Louis & McSorley, Eugene, 2017. "Examining the relationship between visual attention and stated preferences: A discrete choice experiment using eye-tracking," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 238-257.
  31. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
  32. Victor Chernozhukov & Jerry Hausman & Whitney K. Newey, 2019. "Demand analysis with many prices," CeMMAP working papers CWP59/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  33. Rico Krueger & Taha H. Rashidi & Akshay Vij, 2019. "Semi-Parametric Hierarchical Bayes Estimates of New Yorkers' Willingness to Pay for Features of Shared Automated Vehicle Services," Papers 1907.09639, arXiv.org.
  34. Kenneth L. Judd & Ben Skrainka, 2011. "High performance quadrature rules: how numerical integration affects a popular model of product differentiation," CeMMAP working papers CWP03/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  35. David Throsby & Anita Zednik & Jorge E. Araña, 2021. "Public preferences for heritage conservation strategies: a choice modelling approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(3), pages 333-358, September.
  36. Matthew Harding & Ephraim Leibtag & Michael F. Lovenheim, 2012. "The Heterogeneous Geographic and Socioeconomic Incidence of Cigarette Taxes: Evidence from Nielsen Homescan Data," American Economic Journal: Economic Policy, American Economic Association, vol. 4(4), pages 169-198, November.
  37. Rico Krueger & Akshay Vij & Taha H. Rashidi, 2018. "A Dirichlet Process Mixture Model of Discrete Choice," Papers 1801.06296, arXiv.org.
  38. Train, Kenneth, 2016. "Mixed logit with a flexible mixing distribution," Journal of choice modelling, Elsevier, vol. 19(C), pages 40-53.
  39. Martin Burda & Remi Daviet, 2023. "Hamiltonian sequential Monte Carlo with application to consumer choice behavior," Econometric Reviews, Taylor & Francis Journals, vol. 42(1), pages 54-77, January.
  40. Victor Chernozhukov & Whitney K. Newey & Rahul Singh, 2022. "Automatic Debiased Machine Learning of Causal and Structural Effects," Econometrica, Econometric Society, vol. 90(3), pages 967-1027, May.
  41. Hahn, Jinyong & Hausman, Jerry & Lustig, Josh, 2020. "Specification test on mixed logit models," Journal of Econometrics, Elsevier, vol. 219(1), pages 19-37.
  42. Burda, Martin & Prokhorov, Artem, 2014. "Copula based factorization in Bayesian multivariate infinite mixture models," Journal of Multivariate Analysis, Elsevier, vol. 127(C), pages 200-213.
  43. Karabatsos, George & Walker, Stephen G., 2012. "Bayesian nonparametric mixed random utility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1714-1722.
  44. Peter Lenk, 2014. "Bayesian estimation of random utility models," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 20, pages 457-497, Edward Elgar Publishing.
  45. Griffith, Rachel & O'Connell, Martin & Miller, Helen, 2011. "Corporate taxes and the location of intellectual property," CEPR Discussion Papers 8424, C.E.P.R. Discussion Papers.
  46. Norets, Andriy & Pelenis, Justinas, 2022. "Adaptive Bayesian estimation of conditional discrete-continuous distributions with an application to stock market trading activity," Journal of Econometrics, Elsevier, vol. 230(1), pages 62-82.
  47. Burda, Martin & Harding, Matthew & Hausman, Jerry, 2012. "A Poisson mixture model of discrete choice," Journal of Econometrics, Elsevier, vol. 166(2), pages 184-203.
  48. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
  49. I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019. "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 811-843, October.
  50. S. Van Cranenburgh & S. Wang & A. Vij & F. Pereira & J. Walker, 2021. "Choice modelling in the age of machine learning -- discussion paper," Papers 2101.11948, arXiv.org, revised Nov 2021.
  51. Patrick Bajari & Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan, 2009. "A Simple Nonparametric Estimator for the Distribution of Random Coefficients," NBER Working Papers 15210, National Bureau of Economic Research, Inc.
  52. Fernando Bernstein & Sajad Modaresi & Denis Sauré, 2019. "A Dynamic Clustering Approach to Data-Driven Assortment Personalization," Management Science, INFORMS, vol. 67(5), pages 2095-2115, May.
  53. Matzkin, Rosa L., 2019. "Constructive identification in some nonseparable discrete choice models," Journal of Econometrics, Elsevier, vol. 211(1), pages 83-103.
  54. Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2019. "Nonparametric estimation of the random coefficients model: An elastic net approach," Ruhr Economic Papers 824, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
  55. Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
  56. Michael Keane & Nada Wasi, 2013. "Comparing Alternative Models Of Heterogeneity In Consumer Choice Behavior," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(6), pages 1018-1045, September.
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