‘Macroeconometric Models for Portfolio Management’ begins by outlining a portfolio management framework into which macroeconometric models and backtesting investment strategies are integrated. It is followed by a discussion on the theoretical backgrounds of both small and global large macroeconometric models, including data selection, estimation, and applications. Other practical concerns essential to managing a portfolio with decisions driven by macro models are also covered: model validation, forecast combination, and evaluation. The author then focuses on applying these models and their results on managing the portfolio, including making trading rules and asset allocation across different assets and risk management. The book finishes by showing portfolio examples where different investment strategies are used and illustrate how the framework can be applied from the beginning of collecting data, model estimation, and generating forecasts to how to manage portfolios accordingly. This book aims to bridge the gap between academia and practising professionals. Readers will attain a rigorous understanding of the theory and how to apply these models to their portfolios. Therefore, ‘Macroeconometric Models for Portfolio Management’ will be of interest to academics and scholars working in macroeconomics and finance; to industry professionals working in financial economics and asset management; to asset managers and investors who prefer systematic investing over discretionary investing; and to investors who have a strong interest in macroeconomic influences on their portfolio.

This book looks at the distribution of income and wealth and the effects that this has on the macroeconomy, and vice versa. Is a more equal distribution of income beneficial or harmful for macroeconomic growth, and how does the distribution of wealth evolve in a market economy? Taking stock of results and methods developed in the context of the 1990s revival of growth theory, the authors focus on capital accumulation and long-run growth. They show how rigorous, optimization-based technical tools can be applied, beyond the representative-agent framework of analysis, to account for realistic market imperfections and for political-economic interactions. The treatment is thorough, yet accessible to students and nonspecialist economists, and it offers specialist readers a wide-ranging and innovative treatment of an increasingly important research field. The book follows a single analytical thread through a series of different growth models, allowing readers to appreciate their structure and crucial assumptions. This is particularly useful at a time when the literature on income distribution and growth has developed quickly and in several different directions, becoming difficult to overview.

Macroeconomics tries to describe and explain the economywide movement of prices, output, and unemployment. The field has been sharply divided among various schools, including Keynesian, monetarist, new classical, and others. It has also been split between theorists and empiricists. Ray Fair is a resolute empiricist, developing and refining methods for testing theories and models. The field cannot advance without the discipline of testing how well the models approximate the data. Using a multicountry econometric model, he examines several important questions, including what causes inflation, how monetary authorities behave and what are their stabilization limits, how large is the wealth effect on aggregate consumption, whether European monetary policy has been too restrictive, and how large are the stabilization costs to Europe of adopting the euro. He finds, among other things, little evidence for the rational expectations hypothesis and for the so-called non-accelerating inflation rate of unemployment (NAIRU) hypothesis. He also shows that the U.S. economy in the last half of the 1990s was not a new age economy.

In this book Ray Fair expounds powerful techniques for estimating and analyzing macroeconometric models. He takes advantage of the remarkable decrease in computational costs that has occurred since the early 1980s by implementing such sophisticated techniques as stochastic simulation. Testing Macroeconometric Models also incorporates the assumption of rational expectations in the estimation, solution, and testing of the models. And it presents the latest versions of Fair's models of the economies of the United States and other countries. After estimating and testing the U.S. model, Fair analyzes its properties, including those relevant to economic policymakers: the optimal monetary policy instrument, the effect of a government spending reduction on the government deficit, whether monetary policy is becoming less effective over time, and the sensitivity of policy effects to the assumption of rational expectations. Ray Fair has conducted research on structural macroeconometric models for more than twenty years. With interest increasing in the area, this book will be an essential reference for macroeconomists.

The main purpose of this monograph is to give a detailed account of a contemporary, state-of-the art, macroeconometric model that is regularly used for policy advising, and for forecasting in commerce and industry.

The recent financial crisis and the difficulty of using mainstream macroeconomic models to accurately monitor and assess systemic risk have stimulated new analyses of how we measure economic activity and the development of more sophisticated models in which the financial sector plays a greater role. Markus Brunnermeier and Arvind Krishnamurthy have assembled contributions from leading academic researchers, central bankers, and other financial-market experts to explore the possibilities for advancing macroeconomic modeling in order to achieve more accurate economic measurement. Essays in this volume focus on the development of models capable of highlighting the vulnerabilities that leave the economy susceptible to adverse feedback loops and liquidity spirals. While these types of vulnerabilities have often been identified, they have not been consistently measured. In a financial world of increasing complexity and uncertainty, this volume is an invaluable resource for policymakers working to improve current measurement systems and for academics concerned with conceptualizing effective measurement.

At a level suitable for graduate or advanced undergraduates in economics, explains the principles of constructing dynamic macroeconometric models and their use in economic analyses and forecasting. The econometric methodology described is limited to specific applications of time series analysis. The treatment is updated from the 1983 Lectures in Econometrics to account for the end of the Cold War, which raises questions of economic transition in eastern Europe, and the emergence of information technology that has qualitatively changed the speed and breadth of data flows. Annotation copyrighted by Book News, Inc., Portland, OR