Nonparametric IV regression with an Archimedean dependence structure
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Date
2016
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Abstract
This paper provides a characterization of the completeness of a family of distributions
in terms of the copula between the random variables. We give sufficient conditions
for a family of Archimedean copulas to be (boundedly) complete. Some
copulas are typically excluded in nonparametric IV regression since they have
non-square integrable densities. We provide conditions under which we can identify
the nonparametric IV regression model if the dependence structure between
the regressors and instrument variables can be described by an Archimedean
copula.
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Keywords
completeness, nonparametric IV regression model, identification, copula