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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.
One of the major controversies in macroeconomics over the last 30 years has been that on the effectiveness of stabilization policies. However, this debate, between those who believe that this kind of policies is useless if not harmful and those who argue in favor of it, has been mainly theoretical so far. The Rational Expectation Hypothesis, Time-Varying Parameters and Adaptive Control wants to represent a step toward the construction of a common ground on which to empirically compare the two "beliefs" and to do this three strands of literature are brought together. The first strand is the research on time-varying parameters (TVP), the second strand is the work on adaptive control and the third one is the literature on linear stationary models with rational expectations (RE). The material presented in The Rational Expectation Hypothesis, Time-Varying Parameters and Adaptive Control is divided into two parts. Part 1 combines the strand of literature on adaptive control with that on TVP. It generalizes the approach pioneered by Tse and Bar-Shalom (1973) and Kendrick (1981) and one recently used in Amman and Kendrick (2002), where the law of motion of the TVP and the hyperstructural parameters are assumed known, to the case where the hyperstructural parameters are assumed unknown. Part 2 is devoted to the linear single-equation stationary RE model estimated with the error-in-variables (EV) method. It presents a new formulation of this problem based on the use of TVP in an EV model. This new formulation opens the door to a very promising development. All the theory developed in the first part to control a model with TVP can sic et simpliciter be applied to control a model with RE.
Inflation is regarded by the many as a menace that damages business and can only make life worse for households. Keeping it low depends critically on ensuring that firms and workers expect it to be low. So expectations of inflation are a key influence on national economic welfare. This collection pulls together a galaxy of world experts (including Roy Batchelor, Richard Curtin and Staffan Linden) on inflation expectations to debate different aspects of the issues involved. The main focus of the volume is on likely inflation developments. A number of factors have led practitioners and academic observers of monetary policy to place increasing emphasis recently on inflation expectations. One is the spread of inflation targeting, invented in New Zealand over 15 years ago, but now encompassing many important economies including Brazil, Canada, Israel and Great Britain. Even more significantly, the European Central Bank, the Bank of Japan and the United States Federal Bank are the leading members of another group of monetary institutions all considering or implementing moves in the same direction. A second is the large reduction in actual inflation that has been observed in most countries over the past decade or so. These considerations underscore the critical – and largely underrecognized - importance of inflation expectations. They emphasize the importance of the issues, and the great need for a volume that offers a clear, systematic treatment of them. This book, under the steely editorship of Peter Sinclair, should prove very important for policy makers and monetary economists alike.
This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the disturbance driven by Levy process, the research method of M-matrix, and the adaptive control method of the SNN in the context of stability and synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks who wish to learn the core principles, methods, algorithms and applications of SNN.
Monetary policy faces a particularly difficult task in most economies going through structural reforms: having to stabilise fluctuations around the trend, central banks have also to deal with a trend that is itself subjected to shifts, as a result of reforms. This book proposes some perspectives on these issues, with various contributions from both practitioners and academics, emphasising how rather simple techniques can be conveniently used to solve complex problems. Several issues are hence considered, each emphasising a particular aspect of the theme proposed: (i) forecasting inflation, with the experience of the Reserve Bank of New Zealand being taken as an example, since this country went through drastic structural change, (ii) understanding underlying trends of inflation, focusing on expectations and data revision, wage-bargaining process and more generally supply effects, since structural change magnifies them, (iii) formulating policy recommendations, the example taken is the strategy towards the euro for Eastern European countries and (iv) assessing risks of sudden stops.
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.
The use of forward interest rates as a monetary policy indicator is demonstrated, using Sweden 1992-1994 as an example. The forward rates are interpreted as indicating market expectations of the time-path of future interest rates, future inflation rates, and future currency depreciation rates. They separate market expectations for the short-, medium-, and long-term more easily than the standard yield curve. Forward rates are estimated with an extended and more flexible version of Nelson and Siegel’s functional form.
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.
This handbook explains the development and implementation of monetary policy. It examines theories and issues related to the preservation of economic activity and explores why the preservation of economic stability is a principal goal of public policy.
We study the role of uncertainty shocks in explaining unemployment dynamics, separating out the role of aggregate and sectoral channels. Using S&P500 data from the first quarter of 1957 to third quarter of 2014, we construct separate indices to measure aggregate and sectoral uncertainty and compare their effects on the unemployment rate in a standard macroeconomic vector autoregressive (VAR) model. We find that aggregate uncertainty leads to an immediate increase in unemployment, with the impact dissipating within a year. In contrast, sectoral uncertainty has a long-lived impact on unemployment, with the peak impact occurring after two years. The results are consistent with a view that the impact of aggregate uncertainty occurs through a “wait-and-see” mechanism while increased sectoral uncertainty raises unemployment by requiring greater reallocation across sectors.