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Measuring Entrepreneurial Businesses: Current Knowledge and Challenges brings together and unprecedented group of economists, data providers, and data analysts to discuss research on the state of entrepreneurship and to address the challenges in understanding this dynamic part of the economy. Each chapter addresses the challenges of measuring entrepreneurship and how entrepreneurial firms contribute to economies and standards of living. The book also investigates heterogeneity in entrepreneurs, challenges experienced by entrepreneurs over time, and how much less we know than we think about entrepreneurship given data limitations. This volume will be a groundbreaking first serious look into entrepreneurship in the NBER's Income and Wealth series.
In recent decades the American economy has experienced the worst peace-time inflation in its history and the highest unemployment rate since the Great Depression. These circumstances have prompted renewed interest in the concept of business cycles, which Joseph Schumpeter suggested are "like the beat of the heart, of the essence of the organism that displays them." In The American Business Cycle, some of the most prominent macroeconomics in the United States focuses on the questions, To what extent are business cycles propelled by external shocks? How have post-1946 cycles differed from earlier cycles? And, what are the major factors that contribute to business cycles? They extend their investigation in some areas as far back as 1875 to afford a deeper understanding of both economic history and the most recent economic fluctuations. Seven papers address specific aspects of economic activity: consumption, investment, inventory change, fiscal policy, monetary behavior, open economy, and the labor market. Five papers focus on aggregate economic activity. In a number of cases, the papers present findings that challenge widely accepted models and assumptions. In addition to its substantive findings, The American Business Cycle includes an appendix containing both the first published history of the NBER business-cycle dating chronology and many previously unpublished historical data series.
Traditionally, economic growth and business cycles have been treated independently. However, the dependence of GDP levels on its history of shocks, what economists refer to as “hysteresis,” argues for unifying the analysis of growth and cycles. In this paper, we review the recent empirical and theoretical literature that motivate this paradigm shift. The renewed interest in hysteresis has been sparked by the persistence of the Global Financial Crisis and fears of a slow recovery from the Covid-19 crisis. The findings of the recent literature have far-reaching conceptual and policy implications. In recessions, monetary and fiscal policies need to be more active to avoid the permanent scars of a downturn. And in good times, running a high-pressure economy could have permanent positive effects.
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.
Since the Great Depression, researchers and statisticians have recognized the need for more extensive methods for measuring economic growth and sustainability. The recent recession renewed commitments to closing long-standing gaps in economic measurement, including those related to sustainability and well-being. The latest in the NBER’s influential Studies in Income and Wealth series, which has played a key role in the development of national account statistics in the United States and other nations, this volume explores collaborative solutions between academics, policy researchers, and official statisticians to some of today’s most important economic measurement challenges. Contributors to this volume extend past research on the integration and extension of national accounts to establish an even more comprehensive understanding of the distribution of economic growth and its impact on well-being, including health, human capital, and the environment. The research contributions assess, among other topics, specific conceptual and empirical proposals for extending national accounts.
This book outlines and demonstrates problems with the use of the HP filter, and proposes an alternative strategy for inferring cyclical behavior from a time series featuring seasonal, trend, cyclical and noise components. The main innovation of the alternative strategy involves augmenting the series forecasts and back-casts obtained from an ARIMA model, and then applying the HP filter to the augmented series. Comparisons presented using artificial and actual data demonstrate the superiority of the alternative strategy.
It is a great privilege and pleasure to write a foreword for a book honor ing Wolfgang Gaul on the occasion of his sixtieth birthday. Wolfgang Gaul is currently Professor of Business Administration and Management Science and the Head of the Institute of Decision Theory and Management Science, Faculty of Economics, University of Karlsruhe (TH), Germany. He is, by any measure, one of the most distinguished and eminent scholars in the world today. Wolfgang Gaul has been instrumental in numerous leading research initia tives and has achieved an unprecedented level of success in facilitating com munication among researchers in diverse disciplines from around the world. A particularly remarkable and unique aspect of his work is that he has been a leading scholar in such diverse areas of research as graph theory and net work models, reliability theory, stochastic optimization, operations research, probability theory, sampling theory, cluster analysis, scaling and multivariate data analysis. His activities have been directed not only at these and other theoretical topics, but also at applications of statistical and mathematical tools to a multitude of important problems in computer science (e.g., w- mining), business research (e.g., market segmentation), management science (e.g., decision support systems) and behavioral sciences (e.g., preference mea surement and data mining). All of his endeavors have been accomplished at the highest level of professional excellence.