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Spectral Analysis of Economic Time Series. (PSME-1) / Michio Hatanaka, Clive William John Granger.

By: Contributor(s): Material type: TextTextSeries: Princeton Studies in Mathematical Economics ; 2066Publisher: Princeton, NJ : Princeton University Press, [2015]Copyright date: ©1964Description: 1 online resource (318 p.)Content type:
Media type:
Carrier type:
ISBN:
  • 9780691624785
  • 9781400875528
Subject(s): DDC classification:
  • 519.5/5 23
Other classification:
  • online - DeGruyter
Online resources: Available additional physical forms:
  • Issued also in print.
Contents:
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 Β. 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
Summary: 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.
Holdings
Item type Current library Call number URL Status Notes Barcode
eBook eBook Biblioteca "Angelicum" Pont. Univ. S.Tommaso d'Aquino Nuvola online online - DeGruyter (Browse shelf(Opens below)) Online access Not for loan (Accesso limitato) Accesso per gli utenti autorizzati / Access for authorized users (dgr)9781400875528

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 Β. 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

restricted access online access with authorization star

http://purl.org/coar/access_right/c_16ec

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.

Issued also in print.

Mode of access: Internet via World Wide Web.

In English.

Description based on online resource; title from PDF title page (publisher's Web site, viewed 30. Aug 2021)