  We develop and analyze a class of unbiased Monte Carlo estimators for
multivariate jump-diffusion processes with state-dependent drift, volatility,
jump intensity and jump size. A change of measure argument is used to extend
existing unbiased estimators for the inter-arrival diffusion to include
state-dependent jumps. Under standard regularity conditions on the coefficient
and target functions, we prove the unbiasedness and finite variance properties
of the resulting jump-diffusion estimators. Numerical experiments illustrate
the efficiency of our estimators.
