A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions

Chandra R. Bhat () and Patrícia S. Lavieri ()
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Chandra R. Bhat: The University of Texas at Austin
Patrícia S. Lavieri: The University of Texas at Austin

Theory and Decision, 2018, vol. 84, issue 2, No 6, 239-275

Abstract: Abstract In this paper, we propose a general copula approach to accommodate non-normal continuous mixing distributions in multinomial probit models. In particular, we specify a multivariate mixing distribution that allows different marginal continuous parametric distributions for different coefficients. A new hybrid estimation technique is proposed to estimate the model, which combines the advantageous features of each of the maximum simulated likelihood inference technique and Bhat’s maximum approximate composite marginal likelihood inference approach. The effectiveness of our formulation and inference approach is demonstrated through simulation exercises and an empirical application.

Keywords: Copula; Heterogeneity; MACML; Multinomial probit; Choice modeling (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s11238-017-9638-4

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