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University of Pavia
AbstractWorld economies, and especially European ones, have become strongly interconnected in the last decades and a joint modelling is required. We propose here the use of Copulas to build flexible multivariate distributions, since they allow for a rich dependence structure and more flexible marginal distributions that better fit the features of empirical data, such as leptokurtosis. We use our approach to forecast industrial production series in the core EMU countries and we provide evidence that the copula-VAR model outperforms or at worst compares similarly to normal VAR models, keeping the same computational tractability of the latter approach.JEL classification: C13, C32, C51, C53
The aim of this work is to introduce a new econometric methodology for multioutput production frontiers. In the context of a system of frontier equations, we use a flexible multivariate distribution for the inefficiency error term. This multivariate distribution is constructed through a copula function which allows for separate modelling of the marginal inefficiency distributions and the dependence. We pay specific attention to the elicitation of a sensible (improper) prior and provide a simple sufficient condition for posterior propriety. Inference is conducted through a Markov chain Monte Carlo sampler. We use Bayes factors to compare various copula specifications in the empirical context of Dutch dairy farm data, with two outputs.JEL classification: C11, C15, C23, D24
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