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" goes to 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-squared("s") distribution. The estimator also has a Gaussian sequential limit distribution that is obtained first by letting "T" goes to infinity and then letting "N" go to 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). Copyright 2003 Blackwell Publishing Ltd.