This volume presents the most complete collection available of the work of Victor Zarnowitz, a leader in the study of business cycles, growth, inflation, and forecasting.. With characteristic insight, Zarnowitz examines theories of the business cycle, including Keynesian and monetary theories and more recent rational expectation and real business cycle theories. He also measures trends and cycles in economic activity; evaluates the performance of leading indicators and their composite measures; surveys forecasting tools and performance of business and academic economists; discusses historical changes in the nature and sources of business cycles; and analyzes how successfully forecasting firms and economists predict such key economic variables as interest rates and inflation.

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.

The ups and downs of booms and slumps, often referred to as business cycles, are features of all modern economies. This book considers business cycles over three epochs 1870-1913, 1919-1938 and the post-World War II period. It provides an analysis of the key macroeconomic questions relating to economic fluctuations. Why are the ups and down more volatile in some epochs than others? Why are some business cycle shocks more persistent in their effects? Is there an international business cycle? Can present business cycle features predict future patterns? What impact will institutional changes, such as EMU have on future fluctuations?

How can you make wise decisions about your company and your personal future when you have no idea where the economy is headed? The answer is, you can’t. But you can learn how to accurately predict turns in the economy so that you can see the road ahead. And BEATING THE BUSINESS CYCLE shows you how. In BEATING THE BUSINESS CYCLE, Lakshman Achuthan and Anirvan Banerji, the directors of the renowned Economic Cycle Research Institute (ECRI) show how anyone can predict and profit from the inevitable booms and busts of the economy. Why should we believe them? Because while so many economists and financial gurus have failed to predict recessions in the past, ECRI’s forecasts are known for being uncannily accurate. The institute successfully predicted the U.S. recession of 2001 many months before the economists did; the 1990 recession and later recovery; and most recently, the weak U.S. recovery in 2002. ECRI is in constant demand by corporate America and the media. It is the “secret weapon” of companies from Disney to DuPont, the major fund managers, and many central banks. BEATING THE BUSINESS CYCLE is the first book to reveal how decision makers at all levels–managers, small business owners, and individuals–can see into the economy’s future when making key decisions. Should a large company search out new clients and build new factories or stores, or should it consider cost cutting and layoffs? Is it the right time for you to splurge on that luxury vacation or addition to your house, or would it be more prudent to cut back on big expenditures and save money for a rainy day? Written in an easy-to-understand, accessible style, BEATING THE BUSINESS CYCLE reveals which of the hundreds of economic indicators to trust and which ones to trash. It will give you the tools and confidence you need to make the right decisions at the right times–even when the rest of the investing and business world would persuade you otherwise. Whether you are a corporate manager or the owner of a small business, whether you have your money invested in stocks or in your home, BEATING THE BUSINESS CYCLE will give you the edge you need to trump the competition and stay ahead of the crowd.

This paper identifies turning points for the U.S. business cycle using different time series. The model, a multivariate Markov-Swiching model, assumes that each series is characterized by a mixture of two normal distributions (a high and low mean) with switching determined by a common Markov process. The procedure is applied to the series that make up the composite U.S. coincident indicator to obtain business cycle turning points. The business cycle chronology is closer to the NBER reference cycle than the turning points obtained from the individual series using a univariate model. The model is also used to forecast the series, with encouraging results.