ABSTRACT
Consider the model y =Xβ+u, where y is an n-vector of dependent variables, X is a matrix of n×k independent variables, and u is a n-vector of unobserved disturbance. Let z = y−Xb, where b is the least squares estimate of β. The dstatistic tests the hypothesis that the components of u are independent versus the alternative that the components follow a Markov process. The DurbinWatson bounds pertain to the distribution of the d-statistics.
