Evaluating simulation-based approaches and multivariate quadrature on sparse grids in estimating multivariate binary probit models
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DOI: 10.1016/j.econlet.2014.11.021
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- Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
- Keane, Michael P, 1994. "A Computationally Practical Simulation Estimator for Panel Data," Econometrica, Econometric Society, vol. 62(1), pages 95-116, January.
- Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
- Train,Kenneth E., 2009.
"Discrete Choice Methods with Simulation,"
Cambridge Books,
Cambridge University Press, number 9780521766555, September.
- Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
- Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2.
- Geweke, John & Keane, Michael P & Runkle, David, 1994.
"Alternative Computational Approaches to Inference in the Multinomial Probit Model,"
The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 609-632, November.
- John Geweke & Michael P. Keane & David E. Runkle, 1994. "Alternative computational approaches to inference in the multinomial probit model," Staff Report 170, Federal Reserve Bank of Minneapolis.
- Vassilis A. Hajivassiliou & Daniel L. McFadden, 1998.
"The Method of Simulated Scores for the Estimation of LDV Models,"
Econometrica, Econometric Society, vol. 66(4), pages 863-896, July.
- Vassilis A. Hajivassiliou & Daniel L. McFadden, 1993. "The Method of Simulated Scores for the Estimation of LDV Models," Working Papers _023, Yale University.
- V A Hajivassiliou & DL McFadden, 1997. "The Method of Simulated Scores for the Estimation of LDV Models," STICERD - Econometrics Paper Series 328, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Abay, Kibrom A. & Paleti, Rajesh & Bhat, Chandra R., 2013. "The joint analysis of injury severity of drivers in two-vehicle crashes accommodating seat belt use endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 74-89.
- Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996.
"Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results,"
Journal of Econometrics, Elsevier, vol. 72(1-2), pages 85-134.
- Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
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Cited by:
- 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.
- Patil, Priyadarshan N. & Dubey, Subodh K. & Pinjari, Abdul R. & Cherchi, Elisabetta & Daziano, Ricardo & Bhat, Chandra R., 2017. "Simulation evaluation of emerging estimation techniques for multinomial probit models," Journal of choice modelling, Elsevier, vol. 23(C), pages 9-20.
- Abay, Kibrom A. & Berhane, Guush & Taffesse, Alemayehu Seyoum & Koru, Bethlehem & Abay, Kibrewossen, 2016. "Understanding farmers’ technology adoption decisions: Input complementarity and heterogeneity:," ESSP working papers 82, International Food Policy Research Institute (IFPRI).
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More about this item
Keywords
Multivariate probit model; Simulation approaches; GHK simulator; Multivariate quadrature-based approaches; Sparse grids integration;All these keywords.
JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
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