applications in binary-choice models remain scarce. This paper makes use of Bayesian Spatial Probit Models to model and estimate … in nature (an exit had taken place or not), we apply a Bayesian spatial probit model using MCMC estimation on station …

through a heteroskedastic Bayesian spatial probit, which allows the government’s decision to introduce an eco-label to be …

through a heteroskedastic Bayesian spatial probit, which allows the government’s decision to introduce an eco-label to be …

through a heteroskedastic Bayesian spatial probit, which allows the government’s decision to introduce an eco-label to be …

through a heteroskedastic Bayesian spatial probit, which allows the government’s decision to introduce an eco-label to be …

spatial probit with the objective of making accessible to non-users a class of iterative estimation methods that have become … its appeal, applications of the Bayesian paradigm in these settings are still fewer. We provide a primer to the Bayesian …