Spatial effects and common-shocks effects are of increasing empirical importance. Each type of effects has been analyzed separately in a growing literature. This paper considers a joint modeling of both types of effects. Joint modeling allows one to evaluate which type is present or more important. A large number of incidental parameters exist under the joint modeling. Heteroscedasticity is also allowed. The quasi maximum likelihood method (MLE) is proposed to estimate the model. This paper demonstrates that the quasi-MLE can effectively deal with the incidental parameters problem. An inferential theory including consistency, rate of convergence and limiting distributions is developed. The quasi-MLE can be easily implemented via the EM algorithm, as confirmed by the Monte Carlo simulations. The simulation further reveals the excellent finite sample properties of the quasi-MLE. Some potential extensions are discussed.