  The convergence rate in Wasserstein distance is estimated for empirical
measures of ergodic Markov processes, and the estimate can be sharp in some
specific situations.
  The main result is applied to subordinations of typical models excluded by
existing results, which include: stochastic Hamiltonian systems on $\mathbb
R^{n}\times \mathbb R^{m}$, spherical velocity Langevin processes on $\mathbb
R^n\times\mathbb S^{n-1},$ multi-dimensional Wright-Fisher type diffusion
processes, and stable type jump processes.
