Inflation targeting is a monetary-policy strategy that is characterized by an announced numerical inflation target, an implementation of monetary policy that gives a major role to an inflation forecast and has been called forecast targeting, and a high degree of transparency and accountability. It was introduced in New Zealand in 1990, has been very successful in terms of stabilizing both inflation and the real economy, and has, as of 2010, been adopted by about 25 industrialized and emerging-market economies. The chapter discusses the history, macroeconomic effects, theory, practice, and future of inflation targeting.

The optimal weights on indicators in models with partial information about the state of the economy and forward-looking variables are derived and interpreted, both for equilibria under discretion and under commitment. An example of optimal monetary policy with a partially observable potential output and a forward-looking indicator is examined. The optimal response to the optimal estimate of potential output displays certainty-equivalence, whereas the optimal response to the imperfect observation of output depends on the noise in this observation.

Abstract not found

The optimal weights on indicators in models with partial information about the state of the economy and forward-looking variables are derived and interpreted, both for equilibria under discretion and under commitment. The private sector is assumed to have more information about the state of the economy than the policymaker. Certainty equivalence holds for the optimal reaction function in state-space form: thecoefficients are independent of the degree of uncertainty about the state of the economy. However, in the case of commitment, certainty equivalence does not hold for the reaction function in integrative form: the policy instrument cannot be written as a distributed lag of past estimates of past states of the economy. Instead, optimal policy will generally depend on new estimates of past states of the economy, and in ways that depend on the information structure. Furthermore, the usual separation principle does not hold, since the estimation of the state of the economy is not independent of optimization and is, in general, quite complex. We present a general characterization of optimal filtering and control in settings of this kind, and discuss an application of our methods to the problem of the optimal use of “real-time” macroeconomic data in the conduct of monetary policy.

This paper surveys the implications of uncertainty for the design of monetary policy. Among the topics discussed are the impact of imperfect or noisy information on the performance of simple rules, the performance of rules that are robust to the exogenous disturbance processes, the effects of parameter uncertainty, and the implications of robust control. The analysis is conducted using a new Keynesian framework. One finding is that difference rules seem to perform well in the presence of imperfect information about the output gap.

In 2006 all ECB publications will feature a motif taken from the €5 banknote. This paper can be downloaded without charge from

This paper shows how to compute robust Ramsey (aka Stackelberg) plans for linear models with forward looking private agents. We formulate a Bellman equation for the robust plan. We describe robust filtering for when some of the forcing variables (like potential GDP or trend growth) are not observed, and how the decision problem interacts with the filtering problem. We use a ‘new synthesis’ macro model of Woodford as an example.

This paper proves a certainty equivalence result for optimal policy under commitment with symmetric partial information about the state of the economy in a model with forwardlooking variables. This result is used in our previous paper [9], which synthesizes what is known about the case of symmetric partial information, and derives useful general formulas for computation of the optimal policy response coefficients and efficient estimates of the state of the economy in the context of a fairly general forward-looking rational-expectations model. In particular, our proof takes into account that, under commitment, the policymaker can affect the future evolution of the observable variables, and thereby potentially affect the future information available.

This paper proposes an approximation to the optimal policy problem in forward-looking models with regime change that allows for tractable solution for the optimal policy even when the parameters of the model and the current regime are not known with certainty. The linear-quadratic framework is adhered to as much as possible, with a particular emphasis on maintaining the property of separation of estimation and control, which is crucial for maintaining tractability. Generality is achieved by allowing for full Bayesian updating of all aspects of the model, including model parameters, the probability that a regime change has occurred, and the values of all (generally non-normal) shocks hitting the model each period. The methods of this paper provide results that can be quite useful in practice—for example, they fit the policy behavior of the Federal Reserve in the late 1990s very well, which standard methods fail to do. JEL Classification: E52 Version 0.2 — still very preliminary and incomplete

www.elsevier.com/locate/econbase Optimal nonlinear policy: signal extraction with a non-normal prior