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Focuses on economic rather than purely statistical issues, looking at which of the alternative statistical models of seasonality are plausible for economic variables, and asking why seasonal fluctuations in economic variables require special treatment relative to other kinds of fluctuations.
This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling.
Gain the knowledge and skills that can help you exploit instability. No book can help you construct foolproof forecasting systems that will ensure you'll accurately predict economic turning points every time. But with Niemira and Klein's Forecasting Financial and Economic Cycles on hand, you'll be able to significantly strengthen your ability to measure, monitor, and forecast important fluctuations. Part history, it provides you with essential background material on the characteristics and causes of economic volatility. It offers accessible coverage of the classical business cycle, the five basic types of economic cycles as determined by leading economists, and evolving ideas on the forces driving instability—ranging from simple unicausal theories, more complex Keynesian theory, to new classical macroeconomics. In addition, its concise review of America's economic past highlights the lessons that can be learned from the various cycles experienced since shortly before World War II. Part handbook, Forecasting Financial and Economic Cycles presents the full spectrum of statistical techniques used to measure cycles, trends, seasonal patterns, and other vital changes, offering you step-by-step guidance on applying a specific method and detailing its uses and limitations. It goes on to show how youcan adapt particular techniques to assess, track, and predict: Industry cycles—including an objective, tailor-made forecasting tool Regional business cycles—including a survey of regional indicators International business cycles—with an international business cycle chronology Inflation cycles—plus "12 little-known facts" about this complex cycle Financial cycles—covering credit, monetary, and interest rate cycles Stock market cycles—with advice on achieving more disciplined trading Based on outstanding scholarship and years of practical experience, Forecasting Financial and Economic Cycles will serve as an invaluable tool for practitioners like you whose decision-making—and profit margin—depend on accurately assessing today's often uncertain economic climate. "Forecasting Financialand Economic Cycles provides a lively survey of the many ways that cyclical economic activity has been dissected and analyzed. With this book, an astute reader may even be able to anticipate the next cyclical turn." —Samuel D. Kahan, Chief Economist Fuji Securities, Inc. "The definitive book on the most important and enduringfeature of an often mist-bound economic landscape: the business cycle." —Alfred L. Malabre, Jr., Economics Editor, The Wall Street,Journal "Niemira and Klein cover both the theory of economic cyclesand methods for forecasting them. They provide one of the most comprehensive and current reviews of academic studies of economic cycles to be found anywhere." —Anthony F. Herbst, Professor of Finance, The University of Texas at El Paso "This book succeeds as a comprehensive, balanced, and accessible treatment of fluctuations in economic and financial activity. It should prove useful to all those in industry and finance who wish to understand and analyze the trends and changes in the modern dynamic economy." —Victor Zarnowitz, Professor Emeritus of Economics and Finance, University of Chicago
Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time s
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.
This book examines how electoral laws, the timing of election, the ideological orientation of governments, and the nature of competition between political parties influence unemployment, economic growth, inflation, and monetary and fiscal policy. The book presents both a thorough overview of the theoretical literature and a vast amount of empirical evidence.
Specially selected from The New Palgrave Dictionary of Economics 2nd edition, each article within this compendium covers the fundamental themes within the discipline and is written by a leading practitioner in the field. A handy reference tool.
Jeffrey Hirsch discusses how to capture market-beating returns by following specific stock market cycles While predicting the direction of the stock market at any given point is difficult, it's a fact that the market exhibits well-defined and sometimes predictable patterns. While cycles do not repeat exactly all of the time, statistical evidence suggests that cyclical tendencies are very strong and should not be ignored by investors. The Little Book of Stock Market Cycles will show you how to profit from these recurring stock market patterns and cycles. Written by Jeffrey Hirsch, President of the Hirsch Organization and Editor-in-Chief of the Stock Trader's Almanac, this reliable resource explains why these cycles occur, provides the historical evidence behind them, and shows you how to capture consistent profits from them moving forward. In addition to describing his most widely followed cycles and patters, Hirsch also discusses both longer term boom-bust economic cycles and shorter term tendencies involving the best days, weeks, and months of the year to trade the market. The methods found here follow everything from presidential election cycles to the "Santa Claus" effect Written by Jeffrey Hirsch, the pre-eminent authority on market cycles and seasonal patterns The strategies explored are easy-to-implement, and based on research that has proven profitable over the course of time For investors looking to beat the buy-and-hold philosophy, The Little Book of Stock Market Cycles will provide simple, actionable ideas that have stood the test of time and consistently outperformed the market.
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.