Multivariate effect priors in bivariate semiparametric recursive Gaussian models. Thaden, H., Klein, N., & Kneib, T. *Computational Statistics & Data Analysis*, 137:51–66, 2019. Paper doi abstract bibtex Modeling complex relationships and interactions between variables is an ongoing statistical challenge. In particular, the joint modeling of multiple response variables has recently gained interest among methodological and applied researchers. In this article, we contribute to this development by incorporating semiparametric predictors into recursive simultaneous equation models. In particular, we extend the existing framework by imposing effect priors that account for correlation of the effects across equations. This idea can be seen as a generalization of multivariate conditional autoregressive priors used for the analysis of multivariate spatial data. We implement a Gibbs sampler for the estimation and evaluate the model in an elaborate simulation study. Finally, we illustrate the applicability of our approach with real data examples on malnutrition in Asia and Africa as well as the analysis of plant and species richness with respect to environmental diversity.

@article{Thaden2017General,
abstract = {Modeling complex relationships and interactions between variables is an
ongoing statistical challenge. In particular, the joint modeling of multiple
response variables has recently gained interest among methodological and
applied researchers. In this article, we contribute to this development by
incorporating semiparametric predictors into recursive simultaneous equation
models. In particular, we extend the existing framework by imposing effect
priors that account for correlation of the effects across equations. This idea
can be seen as a generalization of multivariate conditional autoregressive
priors used for the analysis of multivariate spatial data.
We implement a Gibbs sampler for the estimation and evaluate the model in
an elaborate simulation study. Finally, we illustrate the applicability of our
approach with real data examples on malnutrition in Asia and Africa as well
as the analysis of plant and species richness with respect to environmental
diversity.},
author = {Thaden, Hauke and Klein, Nadja and Kneib, Thomas},
year = {2019},
title = {Multivariate effect priors in bivariate semiparametric recursive Gaussian models},
url = {https://www.uni-goettingen.de/de/13_Thaden_02_2017/558175.html},
keywords = {econ;phd},
pages = {51--66},
volume = {137},
issn = {01679473},
journal = {Computational Statistics {\&} Data Analysis},
doi = {10.1016/j.csda.2018.12.004},
howpublished = {refereed}
}

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