interest rates, uncertainty, and monetary volatility

ANTHOLOGY Interest Rates, Uncertainty, and Monetary Volatility JOHN E. SILVIA Kemper Financial Services, inc. The channels between money and interest rates have traditionally been examined in terms of liquidity, income, and expected inflation im- pacts. Although the impact of the first three of these factors is well documented, the effect of risk has been surprisingly ignored. The present study enhances previous work by introducing, explicitly, the factor of risk. The research re- ported here was undertaken to test the hypothesis that increasing monetary variability, as a proxy for investor risk, exerts upward pressure on market interest rates. The variability of monetary growth pro- vides the short term investor with informa- tion about the likelihood of future interest rate fluctuations. In this sense, monetary volatility serves as a forward4ooking measure of subsequent interest rate fluctuations and, therefore, risk. As the volatility of money growth increases, as in 1980 and 1981, there will be greater uncertainty with respect to the future direction of Fed policy and, therefore, greater variability in expected future asset returns. For example, does a surprise increase in money signal an easier monetary policy and thereby greater inflation and income effects or, alternatively, will the Fed prise increase in money by term liquidity? For empirical monetary volatility (MVOL) offset the sur- reducing short test purposes, refers to the fluctuations in the observed growth of the money supply measured as the root-mean- squared deviations of money growth relative to a two-year trend of money growth. The regression results for short-run commercial paper (RCP) are given as (t statistics in parentheses): RCPt = 0.20 - 0.12 M t + 0.78 INF t (0.64)(-2.74) (7.25) - 0.02 COPR t + 0.05 GNP72 t + 2.40 MVOL t (-3.80) (3.53) (2.41) where: M represents money (a liquidity proxy); INF represents inflation; COPR represents corporate profits (the real return on capital); and GNP72 is real GNP (the income effect). The R-bar squared is 0.53, the Durbin-Watson 1.74, and the sample period is 1962:2 to 1980:4. Time series methods were employed to pre- filter all the variables to adjust for the auto- regressive behavior of interest rates, hence the lower R-squared statistic. The explanatory variables are significant with the appropriate signs. The regression results indicate that monetary volatility is statistically significant with the expected sign and indeed associated with increases in market interest rates. To further evaluate the significance of monetary volatility, the variable MVOL was dropped from the right-hand side of the equation. The F test for the null hypothesis that the additional explanatory variable, MVOL, has no explanatory power in the commercial paper equation, is rejected at the one percent level. The out-of- sample forecast results indicate that including monetary volatility results in a lower average forecast error (AFE)of- 0.816 and root-mean- squared error (RMSE) of 1.597 for the out-of- sample forecast period 1981:1 to 1982:2 than when monetary volatility is excluded (in that case the AFE = - 1.599 and the RMSE = 2.243). 70

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ANTHOLOGY

Interest Rates, Uncertainty, and Monetary Volatility

JOHN E. SILVIA Kemper Financial Services, inc.

The channels between money and interest rates have traditionally been examined in terms of liquidity, income, and expected inflation im- pacts. Although the impact of the first three of these factors is well documented, the effect of risk has been surprisingly ignored. The present study enhances previous work by introducing, explicitly, the factor of risk. The research re- ported here was undertaken to test the hypothesis that increasing monetary variability, as a proxy for investor risk, exerts upward pressure on market interest rates.

The variability of monetary growth pro- vides the short term investor with informa- tion about the likelihood of future interest rate fluctuations. In this sense, monetary volatility serves as a forward4ooking measure of subsequent interest rate fluctuations and, therefore, risk. As the volatility of money growth increases, as in 1980 and 1981, there will be greater uncertainty with respect to the future direction of Fed policy and, therefore, greater variability in expected future asset returns. For example, does a surprise increase in money signal an easier monetary policy and thereby greater inflation and income effects or, alternatively, will the Fed prise increase in money by term liquidity? For empirical monetary volatility (MVOL)

offset the sur- reducing short test purposes, refers to the

fluctuations in the observed growth of the money supply measured as the root-mean- squared deviations of money growth relative to a two-year trend of money growth.

The regression results for short-run commercial paper (RCP) are given as (t statistics in parentheses):

RCPt = 0.20 - 0.12 M t + 0.78 INF t (0.64)(-2.74) (7.25)

- 0.02 COPR t + 0.05 GNP72 t + 2.40 MVOL t (-3.80) (3.53) (2.41)

where: M represents money (a liquidity proxy); INF represents inflation; COPR represents corporate profits (the real return on capital); and GNP72 is real GNP (the income effect). The R-bar squared is 0.53, the Durbin-Watson 1.74, and the sample period is 1962:2 to 1980:4.

Time series methods were employed to pre- filter all the variables to adjust for the auto- regressive behavior of interest rates, hence the lower R-squared statistic. The explanatory variables are significant with the appropriate signs. The regression results indicate that monetary volatility is statistically significant with the expected sign and indeed associated with increases in market interest rates.

To further evaluate the significance of monetary volatility, the variable MVOL was dropped from the right-hand side of the equation. The F test for the null hypothesis that the additional explanatory variable, MVOL, has no explanatory power in the commercial paper equation, is rejected at the one percent level. The out-of- sample forecast results indicate that including monetary volatility results in a lower average forecast error ( A F E ) o f - 0.816 and root-mean- squared error (RMSE) of 1.597 for the out-of- sample forecast period 1981:1 to 1982:2 than when monetary volatility is excluded (in that case the AFE = - 1.599 and the RMSE = 2.243).

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