RECENT EMPIRICAL STUDIES of the demand for money have - applied distributed lag models to specifications of monetary behavior. One such study by Joseph Adekunle 1 focused on the manner in which adaptive expectations affect portfolio behavior. The present paper is a further investigation into the adaptive expectation model of the demand for money.
One of the explicit properties of the adaptive expectation model is the (theoretical) presence of autocorrelated disturbances. An estimation procedure is utilized here to take into account autocorrelation of the residuals. In particular, an autoregressive mechanism for the serially correlated error term is postulated and estimated simultaneously.2 As numerical examples, regression results are reported for the United States, Canada, Australia, and Norway.
Mr. Villanueva, economist in the Fund’s Central Banking Service, is a graduate of the University of the Philippines and of the University of Wisconsin.
Joseph O. Adekunle, “The Demand for Money: Evidence from Developed and Less Developed Economies,” Staff Papers, Vol. XV (1968), pp. 220–66.
This procedure is superior to the Durbin-Watson test, which yields biased estimates of the autoregressive coefficient. If negative, the estimate is biased toward zero, in which case one might be misled into thinking that serial correlation is not present when in fact it is. A typical procedure to eliminate serial correlation is to use the first differences of the variables, but this assumes that the autoregressive coefficient is equal to 1.
The parameter γ, which lies between 0 and 1, is the adjustment elasticity.
See L.M. Koyck, Distributed Lags and Investment Analysis (Amsterdam, 1954).
This is rather arbitrary; it is only a first approximation.
The instrumental variables used were high-powered money, government expenditures, and exports. The nonlinear least-squares method was the BMDX85 program, based on a Gauss-Newton iterative procedure.
Adekunle, op. cit.