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Copulas are functions that describe the dependence between two or more random variables. This article provides a brief review of copula theory and two areas of economics in which copulas have played important roles: multivariate modeling and partial identification of parameters that depend on the joint distribution of two random variables with fixed or known marginal distributions. We focus on bivariate copulas but provide references on recent advances in constructing higher-dimensional copulas.
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