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Quasi-random simulation of discrete choice models

Citations

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Cited by:

  1. Xiaodong Gong, 2017. "The dynamics of study-work choice and its effect on intended and actual university attainment," Education Economics, Taylor & Francis Journals, vol. 25(6), pages 619-639, November.
  2. Bastin, Fabian & Cirillo, Cinzia & Toint, Philippe L., 2006. "Application of an adaptive Monte Carlo algorithm to mixed logit estimation," Transportation Research Part B: Methodological, Elsevier, vol. 40(7), pages 577-593, August.
  3. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
  4. Mikołaj Czajkowski & Nick Hanley & Jacob LaRiviere, 2016. "Controlling for the Effects of Information in a Public Goods Discrete Choice Model," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(3), pages 523-544, March.
  5. Zsolt Sándor, 2019. "Further evidence on sparse grids-based numerical integration in the mixed logit model," Economics Bulletin, AccessEcon, vol. 39(4), pages 2726-2731.
  6. Dapeng Cui & David Curry, 2005. "Prediction in Marketing Using the Support Vector Machine," Marketing Science, INFORMS, vol. 24(4), pages 595-615, January.
  7. Sarrias, Mauricio, 2016. "Discrete Choice Models with Random Parameters in R: The Rchoice Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i10).
  8. Xiaodong Gong & Robert Breuing, 2011. "Estimating Net Child Care Price Elasticities of Partnered Women With Pre-School Children Using a Discrete Structural Labour Supply-Child Care Model," CEPR Discussion Papers 653, Centre for Economic Policy Research, Research School of Economics, Australian National University.
  9. Prateek Bansal & Vahid Keshavarzzadeh & Angelo Guevara & Shanjun Li & Ricardo A Daziano, 2022. "Designed quadrature to approximate integrals in maximum simulated likelihood estimation [Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariat," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 301-321.
  10. Liu, Henry X. & He, Xiaozheng & Recker, Will, 2007. "Estimation of the time-dependency of values of travel time and its reliability from loop detector data," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 448-461, May.
  11. Train, Kenneth & Wilson, Wesley W., 2008. "Estimation on stated-preference experiments constructed from revealed-preference choices," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 191-203, March.
  12. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
  13. Bhat, Chandra R. & Sidharthan, Raghuprasad, 2011. "A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 940-953, August.
  14. Czajkowski, Mikołaj & Budziński, Wiktor, 2019. "Simulation error in maximum likelihood estimation of discrete choice models," Journal of choice modelling, Elsevier, vol. 31(C), pages 73-85.
  15. Landry, Craig & Remar, Daniel & Twinkle, Roy, 2022. "Economic Value of Restaurant Safety Measures and Propensity to Dine during the COVID-19 Pandemic," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322234, Agricultural and Applied Economics Association.
  16. Ernan Haruvy & Peter T. L. Popkowski Leszczyc, 2010. "Search and Choice in Online Consumer Auctions," Marketing Science, INFORMS, vol. 29(6), pages 1152-1164, 11-12.
  17. Kunwar, Samrat B. & Bohara, Alok K. & Thacher, Jennifer, 2020. "Public preference for river restoration in the Danda Basin, Nepal: A choice experiment study," Ecological Economics, Elsevier, vol. 175(C).
  18. Akinc, Deniz & Vandebroek, Martina, 2018. "Bayesian estimation of mixed logit models: Selecting an appropriate prior for the covariance matrix," Journal of choice modelling, Elsevier, vol. 29(C), pages 133-151.
  19. Pál, László & Sándor, Zsolt, 2023. "Comparing procedures for estimating random coefficient logit demand models with a special focus on obtaining global optima," International Journal of Industrial Organization, Elsevier, vol. 88(C).
  20. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.
  21. Yannis, George & Antoniou, C., 2007. "A mixed logit model for the sensitivity analysis of Greek drivers' behaviour towards enforcement for road safety," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 37, pages 62-77.
  22. Xiaodong Gong & Robert Breunig, 2017. "Childcare Assistance: Are Subsidies or Tax Credits Better?," Fiscal Studies, Institute for Fiscal Studies, vol. 38, pages 7-48, March.
  23. Ziegler Andreas, 2010. "Z-Tests in Multinomial Probit Models under Simulated Maximum Likelihood Estimation: Some Small Sample Properties," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 230(5), pages 630-652, October.
  24. Staus, Alexander, 2008. "Standard and Shuffled Halton Sequences in a Mixed Logit Model," Working Papers 93856, Universitaet Hohenheim, Institute of Agricultural Policy and Agricultural Markets.
  25. repec:sss:wpaper:201404 is not listed on IDEAS
  26. Wüstenhagen, Rolf & Schleich, Joachim & Rennings, Klaus & Heinzle, Stefanie & Brohmann, Bettina, 2009. "What's Driving Sustainable Energy Consumption? A Survey of the Empirical Literature," ZEW Discussion Papers 09-013, ZEW - Leibniz Centre for European Economic Research.
  27. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
  28. Bliemer, Michiel C.J. & Rose, John M., 2013. "Confidence intervals of willingness-to-pay for random coefficient logit models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 199-214.
  29. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
  30. Kawasaki, Tomoya & Hanaoka, Shinya & Nguyen, Long Xuan, 2014. "The valuation of shipment time variability in Greater Mekong Subregion," Transport Policy, Elsevier, vol. 32(C), pages 25-33.
  31. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
  32. Junyi Shen & Yusuke Sakata & Yoshizo Hashimoto, 2006. "A Comparison between Latent Class Model and Mixed Logit Model for Transport Mode Choice: Evidences from Two Datasets of Japan," Discussion Papers in Economics and Business 06-05, Osaka University, Graduate School of Economics.
  33. Munger, D. & L’Ecuyer, P. & Bastin, F. & Cirillo, C. & Tuffin, B., 2012. "Estimation of the mixed logit likelihood function by randomized quasi-Monte Carlo," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 305-320.
  34. Sándor, Z. & Franses, Ph.H.B.F., 2004. "Experimental investigation of consumer price evaluations," Econometric Institute Research Papers EI 2004-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  35. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
  36. 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.
  37. Andreas Ziegler, 2007. "Simulated classical tests in multinomial probit models," Statistical Papers, Springer, vol. 48(4), pages 655-681, October.
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