  We study the problem of computing pairwise statistics, i.e., ones of the form
$\binom{n}{2}^{-1} \sum_{i \ne j} f(x_i, x_j)$, where $x_i$ denotes the input
to the $i$th user, with differential privacy (DP) in the local model. This
formulation captures important metrics such as Kendall's $\tau$ coefficient,
Area Under Curve, Gini's mean difference, Gini's entropy, etc. We give several
novel and generic algorithms for the problem, leveraging techniques from DP
algorithms for linear queries.
