Breaks in money demand.

• Author: Breuer, Janice Boucher

1. Introduction

   During the last twenty years, beginning with the provocative paper by Goldfeld [5] that revealed the case of the "missing money," the question of whether money demand (the relationship between money, income, and an interest rate) is stable has been intensively investigated using a variety of econometric techniques. Currently, the most popular framework for examining the behavior of money demand is the cointegration framework. In this framework, the stationarity of money demand instead of the stability of money demand is evaluated. Earlier tests of the stability of money demand typically centered on whether the coefficient estimates were stable, i.e. not subject to a structural break. These tests did not consider the underlying time series aspects of the variables in money demand or the time series properties of their joint relationship prior to estimation as is now common given the seminal work of Engle and Granger (1).

   Since then, newer tests have focussed on the time series properties of the money demand variables and whether the joint relationship between the variables is stationary, i.e., whether the variables are cointegrated. Engle and Granger [1] and Johansen and Juselius [10] offer cointegration estimation procedures that have been applied by numerous researchers to the money-income-interest rate relationship. The pervasive finding is that money demand is non-stationary (see section II, below). Structural stability has not typically been a facet of investigation. However, the issues of stationarity and stability should not necessarily be treated independently. Failure to take account of structural change may bias the results in favor of non-stationarity, as shown in Perron [16].(1)

   History suggests that the economic environment and monetary institutions, regulations, and operating procedures have changed over time. In the early 1970s, the fixed exchange rate system collapsed when the gold exchange standard was abandoned and the U.S. dollar became a fiat currency. During that same time, the U.S. suffered an oil price shock that produced accelerating inflation and stagnant GDP growth--an outcome that had never before been experienced in post World War II U.S. economic history. In 1979, the Fed changed its operating procedure from primarily targeting interest rates to targeting monetary aggregates. This action combined with Fed chairman Volcker's commitment to fighting inflation has enabled the Federal Reserve's anti-inflation policy to become credible to the private market. In March 1980, the Depository Institutions Deregulation and Monetary Control Act (the Monetary Control Act) was passed which phased out interest rate ceilings and reduced reserve requirements on all types of accounts. This Act promoted competition amongst various types of financial institutions and may have been responsible for the disintermediation that ensued.

   From a policy perspective, it is important to know the behavior of money demand. Both the original Goldfeld [5] finding of the "case of the missing money" and later findings that money demand is non-stationary are troublesome since the ability of policymakers to prevent money market disruptions hinges on whether a money demand relationship that is predictable can be identified. If money demand is not stable, then proper policy conduct may ex post be misguided in light of a structural break and there may be a period of learning before policy is readjusted to its proper course. If money demand is non-stationary, then the Fed may not be able to use such a relationship to target money growth with much accuracy. In this case, the Fed's ability to, ex ante, prevent money market disequilibriums from affecting the economy would be curtailed. This idea follows Poole's [17] analysis. On the other hand, if the Fed's policy is to adjust, ex post, to movements in money demand, it will need to know whether the movements are permanent or transitory. If they are permanent (i.e., money demand is non-stationary), then an adjustment that accommodates "base" drift in the money supply may be warranted. If money demand is stationary so that the movements are transitory, there may be no reason for the Fed to take action unless they desire to speed up (lean with the wind) or slow down (lean against the wind) the adjustment toward a constant equilibrium.

   It is possible that tests that find that money demand is non-stationary may be flawed because the estimation procedures used have not considered a structural break. In our study, we use the econometric technique offered by Gregory and Hansen (G&H) [6] that allows for structural change in a cointegrating framework. We examine whether money demand is stationary in the long run after allowing for a one-time structural break in the money-income-interest rate relationship. The discussion above points to several possible breaks that may be significant for money demand.

   We also use an error correction model with a structural break. Kremers, Ericcson and Dolado [11] find that an error correction model provides more power against the null-hypothesis of "no cointegration" than the standard augmented Dickey-Fuller cointegration test. The standard augmented Dickey-Fuller test imposes a common factor restriction that reduces the information used in estimation relative to that used in an error correction specification. The common factor restriction imposes equality between the short and long run elasticities. Kremers, Ericcson, and Dolado [11] use a bivariate framework to analyze the issue. However, they note that the conclusion holds for generalized cases that include the addition of a constant term, seasonal dummies, additional variables, and additional lags.

   We treat the structural breaks in two ways; (1) we pre-select the breakpoint based on our priors, and (2) we let the data itself determine the breakpoint. In pre-selecting the breakpoints, the structural break is assumed to be caused by an exogenous shock to the money demand data generating process. A criticism of pre-selecting the breakpoint is that we may be data mining, especially if we have visually inspected the money demand relationship to determine an obvious breakpoint. The second treatment does not suffer from this criticism since the breakpoint is estimated endogenously. In this case, the structural break is modelled as a natural manifestation, albeit an outlier, of the data generating process itself. While the endogenous treatment does not suffer from "data mining," it is atheoretical. Ideally, the endogenous estimation procedure will produce a breakpoint that maps into a recognizable historical event, but there is no assurance that this will happen. Moreover, the endogenous estimation procedure may find more than one breakpoint that has a test statistic big enough to surpass the critical value for rejecting "no cointegration." Since there are criticisms of each method, we present the results from both treatments.

   We conduct tests for the stationarity of money demand subject to a structural break using three definitions of money: M1, M2, and credit. M1 and M2 have each been used as a target variable by the Fed and there has been debate over which measure is the appropriate one to use in conducting policy. While credit has not been used as a target variable, Friedman [3, 63] has suggested that it may contain information that "might provide some safeguard against false signals given by the monetary aggregates under conditions of instability affecting the public's demand for money." Our results indicate that a stationary money demand relationship exists after accounting for a structural break at 1980:Q1 for the credit money measure. We find tentative evidence that M1 money demand is stationary subject to a structural break occurring in 1975:Q2. For the M2 money measure, we find, like most other studies, no evidence that money demand is stationary.

2. Literature Review

   Numerous studies have examined money's relationship to income or income and an interest rate using the cointegration methodology. Money measures studied include: M1, M2, and credit. Conclusions...