  In this paper, we consider a simple estimator for tail dependence
coefficients of a max-stable time series and show its asymptotic normality
under a mild condition. The novelty of our result is that this condition does
not involve mixing properties that are common in the literature. More
importantly, our condition is linked to the transition between long and short
range dependence (LRD/SRD) for max-stable time series. This is based on a
recently proposed notion of LRD in the sense of indicators of excursion sets
which is meaningfully defined for infinite-variance time series. In particular,
we show that asymptotic normality with standard rate of convergence and a
function of the sum of tail coefficients as asymptotic variance holds if and
only if the max-stable time series is SRD.
