Spectral analysis of economic time series (PSME-1)

The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devot...

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Bibliographic Details
Main Authors: Granger, C. W. J., Hatanaka, Michio (Author)
Format: eBook
Language:English
Published: Princeton, NJ Princeton University Press 2015, 2015
Series:Princeton studies in mathematical economics
Subjects:
Online Access:
Collection: JSTOR Books - Collection details see MPG.ReNa
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100 1 |a Granger, C. W. J. 
245 0 0 |a Spectral analysis of economic time series (PSME-1)  |h Elektronische Ressource  |c by C.W.J. Granger in association with M. Hatanka 
260 |a Princeton, NJ  |b Princeton University Press  |c 2015, 2015 
300 |a 1 online resource 
505 0 |a Frontmatter -- Foreword -- Preface -- Contents -- Chapter 1. Introduction to the Analysis of Time Series -- Chapter 2. Nature of Economic Time Series -- PART A. STATIONARY TIME SERIES -- Chapter 3. Spectral Theory -- Chapter 4. Spectral Analysis of Economic Data -- Chapter 5. Cross-spectral Analysis -- Chapter 6. Cross-spectral Analysis of Economic Data -- Chapter 7. Processes Involving Feedback -- PART ?. NON-STATIONARY TIME SERIES -- Chapter 8. Series With Trending Means -- Chapter 9. Series with Spectrum Changing with Time -- Chapter 10. Demodulation -- Chapter 11. Non-stationarity and Economic Series -- Chapter 12. Application of Cross-spectral Analysis and Complex Demodulation: Business Cycle Indicators -- Chapter 13. Application of Partial Cross-spectral Analysis: Tests of Acceleration Principle for Inventory Cycle -- Chapter 14. Problems Remaining -- Index 
653 |a Time-series analysis 
653 |a Econometrics 
653 |a BUSINESS & ECONOMICS / General 
653 |a MATHEMATICS / Probability & Statistics / General 
653 |a MATHEMATICS / Applied 
700 1 |a Hatanaka, Michio  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b JSTOR  |a JSTOR Books 
490 0 |a Princeton studies in mathematical economics 
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776 |z 9780691624785 
856 4 0 |u https://www.jstor.org/stable/10.2307/j.ctt183pv0k  |x Verlag  |3 Volltext 
082 0 |a 519.5/5 
520 |a The important data of economics are in the form of time series; therefore, the statistical methods used will have to be those designed for time series data. New methods for analyzing series containing no trends have been developed by communication engineering, and much recent research has been devoted to adapting and extending these methods so that they will be suitable for use with economic series. This book presents the important results of this research and further advances the application of the recently developed Theory of Spectra to economics. In particular, Professor Hatanaka demonstrates the new technique in treating two problems-business cycle indicators, and the acceleration principle existing in department store data.Originally published in 1964.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905