Using a Laplace approximation to estimate the random coefficients logit model by non-linear least squares
Abstract
Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo-random sequences. These methods suffer from difficulties in estimating correlations between parameters and computational limitations such as the curse of dimensionality. This paper provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate extension of the Laplace approximation. Simulation results reveal that our method performs very well, both in terms of accuracy and computational time.Download Info
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP01/06.Length: 20 pp.
Date of creation: Jan 2006
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Handle: RePEc:ifs:cemmap:01/06
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- Patrick Bajari & Han Hong & Stephen Ryan, 2004.
"Identification and Estimation of Discrete Games of Complete Information,"
NBER Technical Working Papers
0301, National Bureau of Economic Research, Inc.
- Stephen Ryan & Patrick Bajari & Han Hong, 2005. "Identification and Estimation of Discrete Games of Complete Information," Computing in Economics and Finance 2005 53, Society for Computational Economics.
- Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-90, July.
- Beggs, S. & Cardell, S. & Hausman, J., 1981. "Assessing the potential demand for electric cars," Journal of Econometrics, Elsevier, vol. 17(1), pages 1-19, September.
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