url
6
Jun
2014

SIMPLE MONETARY POLICY RULES UNDER MODEL UNCERTAINTY: Simple Policy Rules 5

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We conclude from this analysis that small improvements in output and inflation stability may be possible by including more variables (i.e., more information about the state of the economy) in the policy rule. Of course, such benefits may be offset by the lower degree of transparency associated with complicated policy rules. Furthermore, Section 5 will provide evidence that complicated policy rules are somewhat less robust to model uncertainty compared with optimal simple rules.

Rules with Model-Based Forecasts. Simple policy rules that incorporate model-based forecasts of the output gap and inflation rate implicitly respond to all the observed states in the model but remain parsimonious in terms of the number of free parameters in the rule. We have already noted that small reductions in output and inflation volatility can be obtained using complicated rules that respond to a large number of observed state variables. Now we analyze the extent to which these performance gains can be achieved by simple rules that incorporate forecasts of the output gap and inflation rate. In this analysis, we assume the forecasts are model-consistent and are known to the public.

We find three clear results. First, when we augment the class of 3-parameter rules to allow policy to respond additionally to one-quarter and two-quarter inflation forecasts, we find very little improvement in performance relative to optimal rules based only on current and lagged variables. Second, we consider 3-parameter rules in which the current output gap is replaced by model-based forecasts of the future output gap at various horizons. In all four models, rules that respond to the current output gap stabilize output and inflation more effectively than rules that use model-based forecasts of the output gap. Third, we consider 3-parameter rules in which the inflation variable is defined as an average of model-based forecasts as well as current and lagged inflation. In two models (FM and MSR), we find that the optimal inflation variable is an average of current and lagged inflation rates. In the other two models (FRB and TAYMCM), an average of current, lagged, and up to two leads of inflation yields a small improvement in performance.

We conclude from this analysis that small improvements in output and inflation stability may be possible by including more variables (i.e., more information about the state of the economy) in the policy rule. Of course, such benefits may be offset by the lower degree of transparency associated with complicated policy rules. Furthermore, Section 5 will provide evidence that complicated policy rules are somewhat less robust to model uncertainty compared with optimal simple rules. Rules with Model-Based Forecasts. Simple policy rules that incorporate model-based forecasts of the output gap and inflation rate implicitly respond to all the observed states in the model but remain parsimonious in terms of the number of free parameters in the rule. We have already noted that

About The Author

Kevin J. Brandon

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