Different methods of computing exact likelihood function of vector MA (q) model are considered taking special case of vector MA (1) model. A simple method is suggested to compute Po, covariance matrix of estimate of state vector, when Kalman filtering is used to compute exact likelihood function of vector MA(1) model. It is suggested that exact likelihood estimation via Kalman filtering is computationally efficient as compared to Box Hillmer and Tiao method.