Weak convergence of empirical Wasserstein type distances between to real distributions

We estimate the Wasserstein type distance between two continuous distributions $F$ and $G$ on $\mathbb R$ such that the set $\{F = G\}$ is a finnite union of intervals, possibly empty or $\mathbb R$. The positive cost function $\rho$ is not necessarily symmetric and the sample may come from any joint distribution $H$ on $\mathbb R^2$ having marginals $F$ and $G$ with light enough tails with respect to $\rho$ . The rates of weak convergence and the limiting distributions are derived in a wide class of situations including the classical distances $W_1$ and $W_2$. The key new assumption in the case $F = G$ involves the behavior of $\rho$ near $0$, which we assume to be regularly varying with index ranging from $1$ to $2$. Rates are then also regularly varying with powers ranging from $1/2$ to $1$ also affecting the limiting distribution, in addition to $H$