Stephen M. Miller This discussion applies directly to the present problem timating money demand, since the buffer-stock view implie the money market exhibits short -run departures from long-run equilibrium. Equation(1), therefore, represents the long-run(equi librium)money demand, where each variable refers to the trend of the long-run relationship with observed time-series, where the re- siduals measure the short-run deviations from long-run equilibrium Second, modification of the Fair- Jaffee quantitative procedure for estimating markets in disequilibrium suggests that the rates of hange in the interest rate, nominal and real Income. a nd the price level depend on short-run deviations from long-run equilibrium. That is, the residuals from the cointegration regression can be used to estimate directly Equations (4),(5),(5a), and (5b), solving one of the previously mentioned econometric problems Third, the cointegration regression uses simple ordinary least squares, where all variables are potentially endogenous. The error correction model emerges as a restricted vector autoregression. As seen below the estimation of Equations(4),(5),(5a), and (5b )are contained within the class of error-correction models, although with further restrictions 3. Empirical Analysis Considerable debate surrounds the choice of variables to use in the money demand function. Questions arise about the mone- tary aggregate, the interest rate, and the scale variable. I examine three alternatives for the monetary aggregate Ml, MIA, and M2 wo alternatives for the interest rate, the four-to-six-month com- mercial-paper rate (re) and the dividend-to-price ratio (ra); and one alternative for the scale variable, nominal gross national product Y Hendry (1980) and Motley(1988)employ error-correction models, uncon- strained by cointegration equations, to study money demand. Trehan(198 bines cointegration equations with error-correction models to examine Wes oney demand, but does not link the analysis to the estimation of emarket The data are from the Federal Reserve Board Qr data base. Precise definitions of variables are in the 1959 i to 1987: iD. All statistical analysis is performed with the aid of RATS, version 2.03, October9,1956Stephen M. Miller This discussion applies directly to the present problem of es￾timating money demand, since the buffer-stock view implies that the money market exhibits short-run departures from long-run equilibrium.’ Equation (l), therefore, represents the long-run (equi￾librium) money demand, where each variable refers to the trend of the observed series. Cointegration analysis allows the estimation of the long-run relationship with observed time-series, where the re￾siduals measure the short-run deviations from long-run equilibrium. Second, modification of the Fair-Jalfee quantitative procedure for estimating markets in disequilibrium suggests that the rates of change in the interest rate, nominal and real income, and the price level depend on short-run deviations li-om long-run equilibrium. That is, the residuals from the cointegration regression can be used to estimate directly Equations (4), (5), (5a), and (5b), solving one of the previously mentioned econometric problems. Third, the cointegration regression uses simple ordinary least squares, where all variables are potentially endogenous. The error￾correction model emerges as a restricted vector autoregression. As seen below, the estimation of Equations (4), (5), (5a), and (5b) are contained within the class of error-correction models, although with further restrictions. 3. Empirical Analysis Considerable debate surrounds the choice of variables to use in the money demand function.’ Questions arise about the mone￾tary aggregate, the interest rate, and the scale variable. I examine three alternatives for the monetary aggregate, Ml, MIA, and M2; two alternatives for the interest rate, the four-to-six-month com￾mercial-paper rate (rc) and the dividend-to-price ratio (l;i); and one alternative for the scale variable, nominal gross national product (Y), ‘Hendry (1980) and Motley (1988) employ error-correction models, uncon￾strained by cointegration equations, to study money demand. Trehan (1988) com￾bines cointegration equations with error-correction models to examine West Ger￾man money demand, but does not link the analysis to the estimation of markets in disequilibrium. ‘The data are from the Federal Reserve Board Quarterly Econometric Model data base. Precise definitions of variables are in the Appendix. The sample covers 1959:i to 1987:iu. All statistical analysis is performed with the aid of BATS, version 2.03, October 9, 1986. 572