  While the asymptotic relative efficiency (ARE) of Wilcoxon rank-based tests
for location and regression with respect to their parametric Student
competitors can be arbitrarily large, Hodges and Lehmann (1961) have shown that
the ARE of the same Wilcoxon tests with respect to their van der Waerden or
normal-score counterparts is bounded from above by $6/\pi\approx 1.910$. In
this paper, we revisit that result, and investigate similar bounds for
statistics based on Student scores. We also consider the serial version of this
ARE. More precisely, we study the ARE, under various densities, of the
Spearman-Wald-Wolfowitz and Kendall rank-based autocorrelations with respect to
the van der Waerden or normal-score ones used to test (ARMA) serial dependence
alternatives.
