Abstract
In this paper, a Multivariate Spatial Regression model with Endogenous Variables is proposed. In order to deal with endogeneity and spatial dependence, the instrumental variables (IV) methodology and an autoregressive spatial structure, frequently used in econometric applications, are implemented. A Bayesian inference procedure based on simulation schemes designed to obtain samples from the posterior distribution of model parameters is developed. Finally, the methodology is illustrated through an application to the impact of broadband access on the economic sectors.
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