Analyses In Macroeconomic Modelling

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.

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 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.

'An excellent reference volume of this author's work, bringing together articles published over a 25 year span on the statistical analysis of economic time series, large scale macroeconomic modelling and the interface between them.' - Aslib Book Guide This major volume of essays by Kenneth F. Wallis features 28 articles published over a quarter of a century on the statistical analysis of economic time series, large-scale macroeconometric modelling, and the interface between them. The first part deals with time-series econometrics and includes significant early contributions to the development of the LSE tradition in time-series econometrics, which is the dominant British tradition and has considerable influence worldwide. Later sections discuss theoretical and practical issues in modelling seasonality and forecasting with applications in both large-scale and small-scale models. The final section summarizes the research programme of the ESRC Macroeconomic Modelling Bureau, a unique comparison project among economy-wide macroeconometric models.

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.

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.

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.

Macroeconometric models, in many ways the flagships of the economist's profession in the 1960s, came under increasing attack from both theoretical economist and practitioners in the late 1970s. Critics referred to their lack of microeconomic theoretical foundations, ad hoc models of expectations, lack of identification, neglect of dynamics and non-stationarity, and poor forecasting properties. By the start of the 1990s, the status of macroeconometric models had declined markedly, and hadfallen completely out of, and with, academic economics. Nevertheless, unlike the dinosaurs to which they often have been likened, macroeconometric models have never completely disappeared from the scene. This book describes how and why the discipline of macroeconometric modelling continues to play a role for economic policymaking by adapting to changing demands, in response, for instance, to new policy regimes like inflation targeting. Model builders have adopted new insights from economic theory and taken advantage of the methodological and conceptual advances within time series econometrics over the last twenty years. The modelling of wages and prices takes a central part in the book as the authors interpret and evaluate the last forty years of international research experience in the light of the Norwegian 'main course' model of inflation in a small open economy. The preferred model is a dynamic model of incomplete competition, which is evaluated against alternatives as diverse as the Phillips curve, Nickell-Layard wage curves, the New Keynesian Phillips curve, and monetary inflation models on data from the Euro area, the UK, and Norway. The wage price core model is built into a small econometric model for Norway to analyse the transmission mechanism and to evaluate monetary policy rules. The final chapter explores the main sources of forecast failure likely to occur in a practical modelling situation, using the large-scale nodel RIMINI and the inflation models of earlier chapters as case studies.

This book provides an overview of macroeconometric modeling for less developed countries, a description of the structure and performance of Guyana's economy, an empirical testing of the model using annual data for Guyana, and a simulation approach to policy evaluation.

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.