A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems

TLDR

The paper develops efficient GLS/OLS estimators for cointegrating vectors in systems with deterministic components and variables of differing integration orders, and applies them to analyze long‑run U.S. money demand. The estimators are computed via GLS or OLS, and Wald statistics derived from them follow asymptotic chi‑square distributions, enabling the study of U.S.

Abstract

Efficient estimators of cointegrating vectors are presented for systems involving deterministic components and variables of differing, higher orders of integration. The estimators are computed using GLS or OLS, and Wald Statistics constructed from these estimators have asymptotic x2 distributions. These and previously proposed estimators of cointegrating vectors are used to study long-run U.S. money (Ml) demand. Ml demand is found to be stable over 1900-1989; the 95% confidence intervals for the income elasticity and interest rate semielasticity are (.88,1.06) and (-.13, -.08), respectively. Estimates based on the postwar data alone, however, are unstable, with variances which indicate substantial sampling uncertainty.