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The goal of statistical matching is the estimation of the joint distribution of variables not jointly observed in a sample survey but separately available from independent sample surveys.  The lack of joint information on the variables of interest leads to uncertainty about the data generating model. In this paper we propose the use of Bayesian networks to deal with the statistical matching problem since they admit a recursive factorization of a joint distribution useful for evaluating the statistical matching uncertainty in the multivariate context.