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The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
This paper explores Knightian model uncertainty as a possible explanation of the considerable difference between estimated interest rate rules and optimal feedback descriptions of monetary policy. We focus on two types of uncertainty: (i) unstructured model uncertainty reflected in additive shock error processes that result from omitted-variable misspecifications, and (ii) structured model uncertainty, where one or more parameters are identified as the source of misspecification. For an estimated forward-looking model of the U.S. economy, we find that rules that are robust against uncertainty, the nature of which is unspecifiable, or against one-time parametric shifts, are more aggressive than the optimal linear quadratic rule. However, policies designed to protect the economy against the worst-case consequences of misspecified dynamics are less aggressive and turn out to be good approximations of the estimated rule. A possible drawback of such policies is that the losses incurred from protecting against worst-case scenarios are concentrated among the same business cycle frequencies that normally occupy the attention of policymakers.
Recoge: 1. Introduction - 2. Optimal monetary policy with a cost channel of monetary transmission - 3. Optimal robust policy - 4. Caution, activism, or inactiveness? - 5. Robust policy in a dynamic model - 6. Conclusions.
This paper studies how a central bank's preference for robustness against model misspecification affects the design of monetary policy in a New-Keynesian model of a small open economy. Due to the simple model structure, we are able to solve analytically for the optimal robust policy rule, and we separately analyze the effects of robustness against misspecification concerning the determination of inflation, output and the exchange rate. We show that an increased central bank preference for robustness makes monetary policy respond more aggressively or more cautiously to shocks, depending on the type of shock and the source of misspecification.
Oliver Sauter analyzes three aspects of monetary policy under uncertainty. First he shows that the terms risk and uncertainty are often wrongly used as synonyms despite their different meanings. The second aspect is the proper examination and incorporation of uncertainty into a monetary policy framework. The author undertakes systematization with a closer look at each identified form of uncertainty. Thirdly, he focuses on the quantification of uncertainty from two different perspectives, either from a market perspective or from a central bank perspective.
A significant new edition of a text that offers both tools and sample applications; extensive revisions and seven new chapters improve and expand upon the original treatment.
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.
With the collapse of the Bretton Woods system, any pretense of a connection of the world's currencies to any real commodity has been abandoned. Yet since the 1980s, most central banks have abandoned money-growth targets as practical guidelines for monetary policy as well. How then can pure "fiat" currencies be managed so as to create confidence in the stability of national units of account? Interest and Prices seeks to provide theoretical foundations for a rule-based approach to monetary policy suitable for a world of instant communications and ever more efficient financial markets. In such a world, effective monetary policy requires that central banks construct a conscious and articulate account of what they are doing. Michael Woodford reexamines the foundations of monetary economics, and shows how interest-rate policy can be used to achieve an inflation target in the absence of either commodity backing or control of a monetary aggregate. The book further shows how the tools of modern macroeconomic theory can be used to design an optimal inflation-targeting regime--one that balances stabilization goals with the pursuit of price stability in a way that is grounded in an explicit welfare analysis, and that takes account of the "New Classical" critique of traditional policy evaluation exercises. It thus argues that rule-based policymaking need not mean adherence to a rigid framework unrelated to stabilization objectives for the sake of credibility, while at the same time showing the advantages of rule-based over purely discretionary policymaking.
The contributions to this prestigious volume describe important developments in monetary economics and monetary policy during the past half century and to draw lessons from this for the future with chapters from Charles Goodhart and Olivier Blanchard.
Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.