Bücher, Axel2012-07-162012-07-162012-07-16http://hdl.handle.net/2003/2951510.17877/DE290R-14293Nonparametric estimation of tail dependence can be based on a standardization of the marginals if their cumulative distribution functions are known. In this paper it is shown to be asymptotically more efficient if the additional knowledge of the marginals is ignored and estimators are based on ranks. The discrepancy between the two estimators is shown to be substantial for the popular Clayton model. A brief simulation study indicates that the asymptotic conclusions transfer to finite samples.enDiscussion Paper / SFB 823;27/2012asymptotic variancenonparametric estimationrank-based inferencetail copulatail dependence310330620working paper