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A concise but rigorous and thorough introduction to modern macroeconomic theory. This book offers an introduction to modern macroeconomic theory. It is concise but rigorous and broad, covering all major areas in mainstream macroeconomics today and showing how macroeconomic models build on and relate to each other. The self-contained text begins with models of individual decision makers, proceeds to models of general equilibrium without and with friction, and, finally, presents positive and normative theories of economic policy. After a review of the microeconomic foundations of macroeconomics, the book analyzes the household optimization problem, the representative household model, and the overlapping generations model. It examines risk and the implications for household choices and macroeconomic outcomes; equilibrium asset returns, prices, and bubbles; labor supply, growth, and business cycles; and open economy issues. It introduces frictions and analyzes their consequences in the labor market, financial markets, and for investment; studies money as a unit of account, store of value, and medium of exchange; and analyzes price setting in general equilibrium. Turning to government and economic policy, the book covers taxation, debt, social security, and monetary policy; optimal fiscal and monetary policies; and sequential policy choice, with applications in capital income taxation, sovereign debt and default, politically motivated redistribution, and monetary policy biases. Macroeconomic Analysis can be used by first-year graduate students in economics and students in master's programs, and as a supplemental text for advanced courses.
This book gives a practical, applications-oriented account of the latest techniques for estimating and analyzing large, nonlinear macroeconomic models. Ray Fair demonstrates the application of these techniques in a detailed presentation of several actual models, including his United States model, his multicountry model, Sargent's classical macroeconomic model, autoregressive and vector autoregressive models, and a small (twelve equation) linear structural model. He devotes a good deal of attention to the difficult and often neglected problem of moving from theoretical to econometric models. In addition, he provides an extensive discussion of optimal control techniques and methods for estimating and analyzing rational expectations models. A computer program that handles all the techniques in the book is available from the author, making it possible to use the techniques with little additional programming. The book presents the logic of this program. A smaller program for personal microcomputers for analysis of Fair's United States model is available from Urban Systems Research & Engineering, Inc. Anyone wanting to learn how to use large macroeconomic models, including researchers, graduate students, economic forecasters, and people in business and government both in the United States and abroad, will find this an essential guidebook.
This book arose out of research carried out by the authors in the period 1983-1987 whilst at the National Institute of Economic and Social Research. A number of things combined to impart the basic thrust of the research: partly the developments in formulating and estimating rational expectations models, and partly actual developments in the UK economy itself.An application of recent developments in dynamic modelling to a complete macroeconometric model of the UK is presented. Rational expectations modelling, co-integration and disequilibrium modelling are covered. The book also develops computational procedures for obtaining efficient solutions to large-scale models, and illustrates model solutions assuming rational expectations and stochastic simulations. Finally, sections on the analysis of models using optimal control methods illustrate applications of a large-scale econometric model. This section also discusses policy applications, including the derivation of time-consistent policies in the presence of rational expectations, giving quantified illustrations.
Macroeconomic Modelling has undergone radical changes in the last few years. There has been considerable innovation in developing robust solution techniques for the new breed of increasingly complex models. Similarly there has been a growing consensus on their long run and dynamic properties, as well as much development on existing themes such as modelling expectations and policy rules. This edited volume focuses on those areas which have undergone the most significant and imaginative developments and brings together the very best of modelling practice. We include specific sections on (I) Solving Large Macroeconomic Models, (II) Rational Expectations and Learning Approaches, (III) Macro Dynamics, and (IV) Long Run and Closures. All of the contributions offer new research whilst putting their developments firmly in context and as such will influence much future research in the area. It will be an invaluable text for those in policy institutions as well as academics and advanced students in the fields of economics, mathematics, business and government. Our contributors include those working in central banks, the IMF, European Commission and established academics.
This collection of essays applies modern micro-founded macroeconomic models to some of the most important economic policy questions facing monetary and macroeconomic policymakers. Key issues surveyed include: consumption investment; growth and business cycles; the role of government; asset pricing; the interaction of monetary and fiscal policy; open-economy issues; stabilization policy and general equilibrium analysis of emerging market crises. The book includes specially commissioned chapters from recognized authorities.
The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.
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.
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
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.
For Masters and PhD students in EconomicsIn this textbook, the duality between the equilibrium concept used in dynamic economic theory and the stationarity of economic variables is explained and used in the presentation of single equations models and system of equations such as VARs, recursive models and simultaneous equations models.The book also contains chapters on: exogeneity, in the context of estimation, policy analysis and forecasting; automatic (computer based) variable selection, and how it can aid in the specification of an empirical macroeconomic model; and finally, on a common framework for model-based economic forecasting.Supplementary materials and notes are available on the publisher's website.