# The analytical framework

Since Taylor (1993) macroeconomists have relied on simple interest reaction functions to characterise the endogenous response of monetary policymakers to economic fluctuations. Our very own baseline formula for predicting monetary policymakers’ desired interest can be an extension of the classic “Taylor rule”; it talks about the central bank’s forecast of inflation, the growth rate of output, and the output gap. Our rule departs from the classic Taylor specification for the reason that it permits responses to both output gap and the growth rate of output and in addition in that it permits the central bank to react to the forecast of future macroeconomic variables in keeping with the idea that monetary policy changes remember to affect the economy so policymakers ought to be forward-looking within their policy decisions.

The left panel of Figure 1 plots the predicted interest out of this Taylor rule estimated using the forecasts created by the staff of the Federal Reserve before each FOMC meeting (the Greenbooks) in accordance with the actual interest set by the FOMC over almost all of the Greenspan era.

As emphasised by Taylor (1993), a straightforward specification like this can account for a lot of the policy changes over this time around period. However, the predictions of the Taylor rule are noticeably more volatile than actual interest levels. The common size of the predicted change in interest levels (in absolute value) is approximately 60% bigger than actual quarterly changes in interest levels (57 basis points to 35 basis points). Actual interest levels are also a lot more persistent than predicted interest levels (autocorrelations are 0.98 versus 0.93) and the residuals are positively serially correlated.

** Figure 1. **

To take into account this difference between your behaviour of actual interest levels and the ones predicted from baseline Taylor rules, two explanations have already been suggested.

- The first & most common interpretation is policy inertia.

That’s, policymakers usually do not set interest rates add up to the required rate each period but instead move interest levels in a sequence of steps towards the required interest (Clarida et al. 2000).

That is commonly modelled as “interest smoothing”. Applying such formulas to your baseline formula, we look for a very high degrees of interest smoothing (see paper for details). The assumption that interest persistence primarily reflects policy inertia has dominated both empirical and theoretical macroeconomics research.

The next interpretation is that the observed serial correlation in policy rates reflects persistent monetary policy shocks (Rudebusch 2002, 2006). This could be modelled by assuming the errors inside our baseline formula are serially correlated.

The proper panel of Figure 1 shows the fitted values of the Taylor rule beneath the two interpretations of the Fed’s behaviour – an insurance plan inertia and persistent shocks – are essentially indistinguishable to the naked eye (see paper for more precise comparisons and technical details).

Importantly, both interpretations have completely different implications for understanding the determination of monetary policy.

# Differentiating between policy inertia and persistent shocks

In Coibion and Gorodnichenko (2011), we offer robust evidence that policy inertia is a far more likely way to obtain the persistence in interest levels compared to the persistent shocks hypothesis. The main element bits of evidence are:

- Nested specifications

We show that after we enable sufficiently general specifications of both interest smoothing and persistent shocks (i.e. a lot more than first-order processes), specifications of the Taylor rule such as both policy inertia and persistent shocks strongly favour the inertial policy interpretation.

- Conditional identification

An integral difference between your two explanations is that, under policy inertia, the gradual adjustment of interest levels should occur regardless of the underlying way to obtain economic fluctuations, whereas the choice points to additional persistence only after monetary policy shocks. Using exogenous shocks to recognize innovations to the Fed’s forecasts of future macroeconomic conditions that aren’t driven by monetary policy shocks, we continue steadily to find high estimated degrees of interest smoothing, in keeping with the policy inertia interpretation.

- INTEREST Predictability

Rudebusch (2002) argues that if policy inertia was important, then future interest changes ought to be quite predictable, yet he documents that financial futures markets neglect to predict future interest changes beyond the one-quarter horizon. However, the shortcoming of financial markets to predict future interest changes may possibly also reflect uncertainty about the policy rule or even more limited information regarding the economy than what’s open to the Fed. In keeping with this, we find that the assumptions about future interest levels created by the staff of the Fed for every set of Greenbooks execute a significantly better job of predicting future interest changes than private sector forecasts.

# Was the Fed giving an answer to other factors?

Rudebusch (2002) also shows that serially correlated shocks in the Taylor rule should be interpreted as the consequence of the Fed giving an answer to time-specific concerns not controlled for in the Taylor rule. While we are able to never completely eliminate omitted variables, we consider estimates of the Taylor rule augmented with a number of measures of a few of the much more likely candidates for omitted variables.

- Financial market factors

The probably resources of policy actions in a roundabout way linked with output and inflation are credit conditions and financial considerations. However, whenever we include measures of credit spreads, stock prices, and uncertainty in the Taylor rule, these are typically insignificant and don’t qualitatively affect the estimated amount of interest smoothing.

- Real-time forecast revisions

Another omission from the baseline Taylor rule that could potentially and misleadingly result in the looks of policy inertia may be the need for data lags and revisions of Fed forecasts about the existing state. Whenever we augment the Taylor rule to regulate for changes in the Fed’s forecast of macroeconomic conditions, we find no proof significant Fed responses to these measures and the estimates of policy inertia continue being high.

- Private sector forecasts

We also consider the chance that the Fed responds not only to its forecasts of future macroeconomic conditions but also those of the private sector. This may occur if the central bank is unsure about the caliber of its forecasts if they change from those of other agents or if the central bank can be involved about the result of its policy decisions on the expectations of other agents. We find statistically significant evidence that the Federal Reserve does react to deviations of its forecasts from those of the private sector, but controlling for these differences eliminates the data of persistent shocks while leaving the estimate of policy inertia unchanged.

# Conclusion

The historical decisions of the Federal Reserve regarding interest levels, at least through the Greenspan period, consistently indicate very significant inertia in the policymaking process. To the extent that means the exit strategy and the non-interest rate tools utilized by the Fed through the current crisis, our results claim that the policy reversal may very well be gradual, in the lack of additional significant economic shocks.

# References

Clarida, Richard, Jordi Galí, and Mark Gertler (2000), “Monetary Policy Rules and Macroeconomic Stability: Evidence plus some Theory”, Quarterly Journal of Economics 115(1), 147-180.

Coibion, Olivier, and Yuriy Gorodnichenko (2011), “Why are target interest changes so persistent?”, SSRN Working Paper 1738512.

Rudebusch, Glenn D (2006), “Monetary Policy Inertia: Fact or Fiction?”, International Journal of Central Banking, 2(4):85-135.

Taylor, John B (1993), “Discretion versus Policy Rules used”, Carnegie Rochester Conference Series on Public Policy, 39:195-214.