Cointegration vector estimation by panel DOLS and long-run money demand

We study the panel dynamic ordinary least square (DOLS) estimator of a homogeneous cointegration vector for a balanced panel of N individuals observed over T time periods. Allowable heterogeneity across individuals include individual-specific time trends, individual-specific fixed effects and time-specific effects. The estimator is fully parametric, computationally convenient, and more precise than the single equation estimator. For fixed N as T --> infinity, the estimator converges to a function of Brownian motions and the Wald statistic for testing a set of s linear constraints has a limiting chi(2)(s) distribution. The estimator also has a Gaussian sequential limit distribution that is obtained first by letting T --> infinity and then letting N --> infinity. In a series of Monte-Carlo experiments, we find that the asymptotic distribution theory provides a reasonably close approximation to the exact finite sample distribution. We use panel DOLS to estimate coefficients of the long-run money demand function from a panel of 19 countries with annual observations that span from 1957 to 1996. The estimated income elasticity is 1.08 (asymptotic s.e. = 0.26) and the estimated interest rate semi-elasticity is -0.02 (asymptotic s.e. = 0.01).