  In this paper we establish asymptotic simultaneous confidence bands for
copulas based on the local linear kernel estimator proposed by Chen and Huang
[1]. For this, we prove under smoothness conditions on the copula function, a
uniform in bandwidth law of the iterated logarithm for the maximal deviation of
this estimator from its expectation. We also show that the bias term converges
uniformly to zero with a precise rate. The performance of these bands is
illustrated in a simulation study. An application based on pseudo-panel data is
also provided for modeling dependence.
