Our answer: Not so well. We reached that conclusion after reviewing recent research on the role of technology as a source of economic fluctuations. The bulk of the evidence suggests a limited role for aggregate technology shocks, pointing instead to demand factors as the main force behind the strong positive comovement between output and labor input measures.
Bayesian econometric methods have enjoyed an increase in popularity in recent years. Econometricians, empirical economists, and policymakers are increasingly making use of Bayesian methods. This handbook is a single source for researchers and policymakers wanting to learn about Bayesian methods in specialized fields, and for graduate students seeking to make the final step from textbook learning to the research frontier. It contains contributions by leading Bayesians on the latest developments in their specific fields of expertise. The volume provides broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing. It reviews the state of the art in Bayesian econometric methodology, with chapters on posterior simulation and Markov chain Monte Carlo methods, Bayesian nonparametric techniques, and the specialized tools used by Bayesian time series econometricians such as state space models and particle filtering. It also includes chapters on Bayesian principles and methodology.
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.
The business cycle or economic cycle refers to the periodic fluctuations of economic activity about its long term growth trend. The cycle involves shifts over time between periods of relatively rapid growth of output (recovery and prosperity), alternating with periods of relative stagnation or decline (contraction or recession). These fluctuations are often measured using the real gross domestic product. One of the government's main roles is to smooth out the business cycle and reduce its fluctuations. To call those alternances 'cycles' is rather misleading as they don't tend to repeat at fairly regular time intervals. Most observers find that their lengths (from peak to peak, or from trough to trough) vary, so that cycles are not mechanical in their regularity. Since no two cycles are alike in their details, some economists dispute the existence of cycles and use the word 'fluctuations' (or the like) instead. Others see enough similarities between cycles that the cycle is a valid basis of studying the state of the economy. A key question is whether or not there are similar mechanisms that generate recessions and/or booms that exist in capitalist economies so that the dynamics that appear as a cycle will be seen again and again. This new book presents leading-edge research in this field.
This is the most sophisticated and up-to-date econometric analysis of business cycles now available. Francis Diebold and Glenn Rudebusch have long been acknowledged as leading experts on business cycles. And here they present a highly integrative collection of their most important essays on the subject, along with a detailed introduction that draws together the book's principal themes and findings. Diebold and Rudebusch use the latest quantitative methods to address five principal questions about the measurement, modeling, and forecasting of business cycles. They ask whether business cycles have become more moderate in the postwar period, concluding that recessions have, in fact, been shorter and shallower. They consider whether economic expansions and contractions tend to die of "old age." Contrary to popular wisdom, they find little evidence that expansions become more fragile the longer they last, although they do find that contractions are increasingly likely to end as they age. The authors discuss the defining characteristics of business cycles, focusing on how economic variables move together and on the timing of the slow alternation between expansions and contractions. They explore the difficulties of distinguishing between long-term trends in the economy and cyclical fluctuations. And they examine how business cycles can be forecast, looking in particular at how to predict turning points in cycles, rather than merely the level of future economic activity. They show here that the index of leading economic indicators is a poor predictor of future economic activity, and consider what we can learn from other indicators, such as financial variables. Throughout, the authors make use of a variety of advanced econometric techniques, including nonparametric analysis, fractional integration, and regime-switching models. Business Cycles is crucial reading for policymakers, bankers, and business executives.
Dornbusch, Fischer, and Startz has been a long-standing, leading intermediate macroeconomic theory text since its introduction in 1978. This revision retains most of the text's traditional features, including a middle-of-the-road approach and very current research, while updating and simplifying the exposition. A balanced approach explains both the potential and limitations of economic policy. Macroeconomics employs a model-based approach to macroeconomic analysis and demonstrates how various models are connected with the goal of giving students the capacity to analyze current economic issues in the context of an economic frame of reference. The only pre-requisite continues to be principles of economics.
The NBER Macroeconomics Annual presents pioneering work in macroeconomics by leading academic researchers addressed to a broad audience of public policymakers as well as to the academic community. Each paper is followed by comments and discussion to give a more complete context for the views expressed. The 2004 edition features a range of papers aimed at providing coherent and informative answers to such important questions as the effect of federal government debt on interest rates; the stochastic dimension of the American economy; the role of technology as a source of economic fluctuations; and the interaction of capital flows, fiscal policy, and monetary policies in developing countries, emerging markets, and OECD countries.
Summarizes developments and techniques in the field. It highlights areas such as sample surveys, nonparametic analysis, hypothesis testing, time series analysis, Bayesian inference, and distribution theory for applications in statistics, economics, medicine, biology, and engineering.
Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
