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This tutorial is designed to introduce readers to Bayesian variants of the standard SAR and SEM models that are the most widely used and applied models in spatial econometrics. Particular attention is paid to the mathematical derivations required to obtain the full conditional distributions...
Persistent link: https://www.econbiz.de/10012723417
In this paper we propose a Bayesian estimation approach for a spatial autoregressive logit specification. Our approach relieson recent advances in Bayesian computing, making use of Pólya-Gamma sampling for Bayesian Markov-chain Monte Carlo algorithms.The proposed specification assumes that the...
Persistent link: https://www.econbiz.de/10012061923
We use Bayesian Model Averaging (BMA) to evaluate the robustness of determinants of economic growth in a new dataset of 255 European regions in the 1995-2005 period. We use three different specifications based on (1) the cross-section of regions, (2) the cross-section of regions with country...
Persistent link: https://www.econbiz.de/10012765299
In many manuscripts, researchers use multivariable logistic regression to adjust for potential confounding variables when estimating a direct relationship of a treatment or exposure on a binary outcome. After choosing how variables are entered into that model, researchers can calculate an...
Persistent link: https://www.econbiz.de/10015202692
This article describes an R package bqror that estimates Bayesian quantile regression for ordinal models introduced in Rahman (2016). The paper classifies ordinal models into two types and offers computationally efficient, yet simple, MCMC algorithms for estimating ordinal quantile regression....
Persistent link: https://www.econbiz.de/10013210768
This study proposes a Bayesian approach for exact finite-sample inference of an instrument-free estimation method that builds upon joint estimation using copulas to deal with endogenous covariates. Although copula approaches with applications to handle regressor-endogeneity have been frequently...
Persistent link: https://www.econbiz.de/10014243806
While demand models require a sound understanding of economic processes and should be flexible enough to capture nonlinearities, endogeneity can greatly hinder the identification of (nonlinear) causal relationships. To tackle these issues, we extend the instrument-free Gaussian copula approach...
Persistent link: https://www.econbiz.de/10014344614
This paper develops new econometric methods to estimate hospital quality and other models with discrete dependent variables and non-random selection. Mortality rates in patient discharge records are widely used to infer hospital quality. However, hospital admission is not random and some...
Persistent link: https://www.econbiz.de/10014165225
We develop a Markov Chain Monte Carlo algorithm for estimating nested logit models in a Bayesian framework. Appropriate "heating target" and reparametrization techniques are adopted for fast mixing. For illustrative purposes, we have implemented the algorithm on two real-life examples involving...
Persistent link: https://www.econbiz.de/10014113986
We develop a Markov Chain Monte Carlo algorithm for estimating nested logit models in a Bayesian framework. Appropriate "heating target" and reparametrization techniques are adopted for fast mixing. For illustrative purposes, we have implemented the algorithm on two real-life examples involving...
Persistent link: https://www.econbiz.de/10014112400