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Mr. Makin, Consultant in the Research Department when this paper was prepared, is Professor of Economics at the University of Washington in Seattle and a Research Associate with the National Bureau of Economic Research. This article represents a part of a large body of work that he has undertaken investigating the effects of monetary policy and associated phenomena, both nationally and internationally. He is a graduate of Trinity College (Hartford, Connecticut) and the University of Chicago.
Long before the investigations discussed here, Irving Fisher reported, based on an investigation of market interest rates during the late nineteenth and early twentieth centuries in London, New York, Berlin, Calcutta, and Tokyo, that “the real rate of interest in terms of commodities is from seven to thirteen times as variable as the market rate of interest expressed in terms of money” (Fisher (1930), p. 415).
Mishkin (1981) found a significant negative impact upon the real rate of a lagged actual (consumer price index) inflation rate taken as a proxy for anticipated inflation. An autoregressive integrated moving average (ARIMA) (0,1,1) inflation model with a seasonal MA-1 term also provided an expected inflation proxy with a significant negative impact on the real rate.
Alamouti (1980) provides a similar description of the determination of the real rate. Determination of the real rate in this manner is suggested directly by the full title of Fisher’s (1930) classic—The Theory of Interest as Determined by Impatience to Spend Income and Opportunity to Invest it.
This view of dynamic adjustment to monetary shocks is investigated empirically for a number of developing countries in Khan (1980).
Since actual money growth less anticipated money growth is written as
Both figures are expressed as seasonally adjusted annual rates. Net funds raised in U.S. credit markets are based on data drawn from the U.S. Federal Reserve Board’s Flow-of-Funds Accounts. See Federal Reserve Bulletin, Table 1.58, “Funds Raised in U.S. Credit Markets,” Line 60.
Cornell is clearly thinking of shocks to the monetary base in the form of shortages or excesses of bank reserves.
The first number in parentheses indicates the order of the autoregressive process, and the second number the order of the moving average.
The chi-square test statistic for the hypothesis that the residuals of the ARMA(1,5) model is 6.84 with 14 degrees of freedom, which implies a significance level of 0.94. The model was estimated using quarterly data for the period extending from the first quarter of 1959 to the fourth quarter of 1980.
Hendry also suggests that identifying the correct order of error autocorrelation is more important than the form (AR or MA). More specifically, had the true error process been ARMA (0,1), an ARMA (1,0) would do reasonably well. But since the true process in equation (9) was ARMA (1,3), ARMA (1,0) represents a serious misspecification.
A value above unity is anticipated if tax effects articulated by Darby (1975), Tanzi (1976), and Feldstein (1976) are considered. See Tanzi (1980) for a discussion of these articles and others that investigate the quantitative impact of changing inflationary expectations on nominal interest. Tanzi argues that “fiscal illusion,” or failure to account for taxes, may be responsible for lower-than-expected coefficients obtained when nominal interest rates are regressed on anticipated inflation.
Levi and Makin (1978, 1979, 1981) have investigated a number of these effects in a model including a Mundell-Tobin effect. This paper, however, adds consideration of money surprise effects on the real rate.
The problem of inference here is complicated by the fact that the Mundell-Tobin hypothesis hinges upon the difference of the coefficient of anticipated inflation from unity and not from zero. However, both the incorporation of a change in anticipated inflation into nominal interest and the real impact under the Mundell-Tobin hypothesis are expected to be permanent. This generates a prior hypothesis of persistence with no subsequent reversal that is not contradicted by the data.
That is, the standard deviation across sample participants of the expected rate of inflation as reported in surveys conducted by the Philadelphia Inquirer under the guidance of Joseph Livingston and compiled semiannually by the Federal Reserve Bank of Philadelphia.
Despite some correlation with FDOG, anticipated inflation remains a highly significant explanatory variable in an equation such as (10). The F-statistic for the significance of including anticipated inflation in equation (10) is 14.65, well above the critical value of 7.01 required for significance at the 0.01 level.
It is important to realize that total borrowing relative to GNP—and not the government budget deficit relative to GNP—is included in equation (10). If the budget deficit relative to GNP were to be employed in place of the variable used in equation (10), the estimated coefficient would indicate that larger deficits cause interest rates to fall. The reason for this seemingly odd result is that during the 1959-80 sample period, government deficits typically rose in recessions when private borrowing fell. As the latter category is roughly three times government borrowing, the net effect is a reduction in total credit demand. Therefore, a larger government budget deficit is serving as a proxy for a fall in total credit demand, which, in turn, results in a drop in the real rate.
The term “budget deficits” refers here only to government borrowing that raises the ratio of total borrowing to GNP.