A Full Gibbs Sampler for a Multinomial Probit Model with Endogeneity
نویسندگان
چکیده
We introduce methods for estimating a Bayesian multinomial probit switching model for unordered selection and response categories via a fully Gibbsian estimation strategy. We achieve this through the use of marginal data augmentation and a modified Imai/van Dyk-type prior for the covariance matrix. Compared to related work that requires a Metropolis step, this method improves computational efficiency and overall simplicity. Additionally, we modify the Chib method to estimate Bayes factors. The estimation strategy is applied to simulated data and is used to model retirement outcomes for groups with differing retirement preferences in the Wisconsin Longitudinal Study.
منابع مشابه
The Analysis of Bayesian Probit Regression of Binary and Polychotomous Response Data
The goal of this study is to introduce a statistical method regarding the analysis of specific latent data for regression analysis of the discrete data and to build a relation between a probit regression model (related to the discrete response) and normal linear regression model (related to the latent data of continuous response). This method provides precise inferences on binary and multinomia...
متن کاملAn exact likelihood analysis of the multinomial probit model
We develop new methods for conducting a finite sample, likelihood-based analysis of the multinomial probit model. Using a variant of the Gibbs sampler, an algorithm is developed to draw from the exact posterior of the multinomial probit model with correlated errors. This approach avoids direct evaluation of the likelihood and, thus, avoids the problems associated with calculating choice probabi...
متن کاملForecasting adoption of ultra-low-emission vehicles using the GHK simulator and Bayes estimates of a multinomial probit model
In this paper we use Bayes estimates of a multinomial probit model with fully flexible substitution patterns to forecast consumer response to ultra-low-emission vehicles. In this empirical application of the probit Gibbs sampler, we use statedpreference data on vehicle choice from a Germany-wide survey of potential lightduty-vehicle buyers using computer-assisted personal interviewing. We show ...
متن کاملForecasting Adoption of Ultra-Low-Emission Vehicles Using Bayes Estimates of a Multinomial Probit Model and the GHK Simulator
In this paper we use Bayes estimates of a multinomial probit model with fully flexible substitution patterns to forecast consumer response to ultra-low-emission vehicles. In this empirical application of the probit Gibbs sampler, we use stated-preference data on vehicle choice from a Germany-wide survey of potential light-duty-vehicle buyers using computer-assisted personal interviewing. We sho...
متن کاملSymmetric Bayesian Multinomial Probit Models
Standard Bayesian multinomial probit (MNP) models that are fit using different base categories can give different predictions. Therefore, we propose the symmetric MNP model, which does not make reference to a base category. To achieve this, we employ novel sum-to-zero identifying restrictions on the latent utilities and regression coefficients that define the model. This results in a model whos...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009