  Consider the metric space $(\mathcal{P}_2(\mathbb{R}^d),W_2)$ of square
integrable laws on $\mathbb{R}^d$ with the topology induced by the
2-Wasserstein distance $W_2$. Let $\Phi: \mathcal{P}_2( \mathbb{R}^d) \to
\mathbb{R}$ be a function and $\mu_N$ be the empirical measure of a sample of
$N$ random variables distributed as $\mu$. The main result of this paper is to
show that under suitable regularity conditions, we have \[ |\Phi(\mu) -
\mathbb{E}\Phi(\mu_N)|= \sum_{j=1}^{k-1}\frac{C_j}{N^j} + O(\frac{1}{N^k}), \]
for some positive constants $C_1, \ldots, C_{k-1}$ that do not depend on $N$,
where $k$ corresponds to the degree of smoothness. We distinguish two cases: a)
$\mu_N$ is the empirical measure of $N$-samples from $\mu$; b) $\mu$ is a
marginal law of McKean-Vlasov stochastic differential equation in which case
$\mu_N$ is an empirical law of marginal laws of the corresponding particle
system. The first case is studied using functional derivatives on the space of
measures. The second case relies on an It\^{o}-type formula for the flow of
probability measures and is intimately connected to PDEs on the space of
measures, called the master equation in the literature of mean-field games. We
state the general regularity conditions required for each case and analyse the
regularity in the case of functionals of the laws of McKean-Vlasov SDEs.
Ultimately, this work reveals quantitative estimates of propagation of chaos
for interacting particle systems. Furthermore, we are able to provide weak
propagation of chaos estimates for ensembles of interacting particles and show
that these may have some remarkable properties.
