We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We take into account the endogeneity through a system of simultaneous equations where a conditional correlation between the...

The gravity model is a workhorse tool that has been widely used in international trade. However, one empirical question that frequently arises is related to the conceptualization and measurement of distance. To overcome this limitation, our study proposes an index of distance based on...

Identifying the true determinants of export diversification is difficult as there exists no comprehensive theoretical or empirical framework to capture all potential factors in their entirety. This paper uses Bayesian Model Averaging to uncover the true long-term roots of export diversification...

The world meat market demands competitiveness and optimal livestock replacement decisions can help to achieve this goal. We introduce a novel discrete stochastic dynamic programming framework to support a manager's decision-making process of whether to sell or keep fattening animals in the beef...

We introduce a Bayesian instrumental variable procedure with spatial random effects that handles endogeneity, and spatial dependence with unobserved heterogeneity. We find through a limited Monte Carlo experiment that our proposal works well in terms of point estimates and prediction. Then, we...