We examine the performance and robustness properties of monetary policy rules in an estimated macroeconomic model in which the economy undergoes structural change andwhere private agents and the central bank possess imperfect knowledge about the true structure of the economy. Policymakers follow an interest rate rule aiming to maintain price stability and to minimize fluctuations of unemployment around its natural rate but areuncertain about the economy's natural rates of interest and unemployment and how private agents form expectations. In particular, we consider two models of expectations formation :rational expectations and learning. We show that in this environment the ability to stabilize the real side of the economy is significantly reduced relative to an economy under rational expectations with perfect knowledge. Furthermore, policies that would be optimal under perfect knowledge can perform very poorly if knowledge is imperfect. Efficient policies that take account of private learning and misperceptions of natural rates call for greater policy inertia, a more aggressive response to inflation, and a smaller response to the perceived unemployment gap than would be optimal if everyone had perfect knowledge of the economy. We show that such policies are quite robust to potential misspecification of private sector learning and the magnitude of variation in natural rates.

We examine the performance and robustness of monetary policy rules when the central bank and the public have imperfect knowledge of the economy and continuously update their estimates of model parameters. We find that versions of the Taylor rule calibrated to perform well under rational expectations with perfect knowledge perform very poorly when agents are learning and the central bank faces uncertainty regarding natural rates. In contrast, difference rules, in which the change in the interest rate is determined by the inflation rate and the change in the unemployment rate, perform well when knowledge is both perfect and imperfect.

Based on lectures given as part of The Stone Lectures in Economics, this book discusses the problem of formulating monetary policy in practice, under the uncertain circumstances which characterize the real world. The first lecture highlights the limitations of decision rules suggested by the academic literature and recommends an approach involving, first, a firm reliance on the few fundamental and robust results of monetary economics and, secondly, a pragmatic attitude to policy implementation, taking into consideration lessons from central banking experience. The second lecture revisits Milton Friedman's questions about the effects of active stabilization policies on business cycle fluctuations. It explores the implications of a simple model where the policy maker has imperfect knowledge about potential output and the private sector forms expectations according to adaptive learning. This lecture shows that imperfect knowledge limits the scope for active stabilization policy and strengthens the case for conservatism.

Over the past fifteen years, a significant number of industrialized and middle-income countries have adopted inflation targeting as a framework for monetary policymaking. As the name suggests, in such inflation-targeting regimes, the central bank is responsible for achieving a publicly announced target for the inflation rate. While the objective of controlling inflation enjoys wide support among both academic experts and policymakers, and while the countries that have followed this model have generally experienced good macroeconomic outcomes, many important questions about inflation targeting remain. In Inflation Targeting, a distinguished group of contributors explores the many underexamined dimensions of inflation targeting—its potential, its successes, and its limitations—from both a theoretical and an empirical standpoint, and for both developed and emerging economies. The volume opens with a discussion of the optimal formulation of inflation-targeting policy and continues with a debate about the desirability of such a model for the United States. The concluding chapters discuss the special problems of inflation targeting in emerging markets, including the Czech Republic, Poland, and Hungary.

This paper investigates the role that imperfect knowledge about the structure of the economy plays in the formation of expectations, macroeconomic dynamics, and the efficient formulation of monetary policy. Economic agents rely on an adaptive learning technology to form expectations and to update continuously their beliefs regarding the dynamic structure of the economy based on incoming data. The process of perpetual learning introduces an additional layer of dynamic interaction between monetary policy and economic outcomes. We find that policies that would be efficient under rational expectations can perform poorly when knowledge is imperfect. In particular, policies that fail to maintain tight control over inflation are prone to episodes in which the public's expectations of inflation become uncoupled from the policy objective and stagflation results, in a pattern similar to that experienced in the United States during the 1970s. Our results highlight the value of effective communication of a central bank's inflation objective and of continued vigilance against inflation in anchoring inflation expectations and fostering macroeconomic stability.