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This paper discusses the role of forecasts in the control of inflation. Much has been made of variations on the so-called Taylor rule for inflation control. Forward-looking Taylor rules are reconciled with optimal control using a class of rules described as error-correcting Taylor rules.

This paper investigates the econometric properties of the Taylor (1993) rule applied to U.S., Australian and Swedish data to judge its empirical relevance. Little attention has been paid to the time series properties of the data underlying interest rate rules, nor the estimations themselves, despite the rise in popularity of Taylor-like rules in both empirical and theoretical work. Unit root tests indicate that the variables commonly used in such modelling are likely to be integrated of order one or near integrated. Given that the variables in the Taylor rule are integrated of order one or near integrated processes, cointegration is a necessary condition both for consistent estimation of the parameters of the model and compatibility between the model and the data. Tests find little support for cointegration and, together with an out-of-sample forecast exercise, suggest that we should have serious doubts about the Taylor rule as a reasonable description of how monetary policy is conducted in the countries considered in this study. Parameter estimates from the standard Taylor rule regressions are therefore likely to be inconsistent and caution should be taken before for central bank policy is evaluated using such methods.

This paper contributes to the analysis of monetary policy in the face of financial instability. In particular, we extend the standard new Keynesian dynamic stochastic general equilibrium (DSGE) model with sticky prices to include a financial system. Our simulations suggest that if financial instability affects output and inflation with a lag and if the central bank has privileged information about credit risk, monetary policy that responds instantly to increased credit risk can trade off more output and inflation instability today for a faster return to the trend than a policy that follows the