A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions. (English) Zbl 1395.62111
Summary: 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.
MSC:
| 62H05 | Characterization and structure theory for multivariate probability distributions; copulas |
| 60E05 | Probability distributions: general theory |
| 91B06 | Decision theory |
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