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Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series

Ce livre peut être téléchargé sur votre Mac ou appareil iOS avec iBooks, et sur votre ordinateur avec iTunes. Les livres peuvent être lus sur votre Mac ou appareil iOS avec iBooks.


In modern economies, time series play a crucial role at all levels of activity. They are used by decision makers to plan for a better future, by governments to promote prosperity, by central banks to control inflation, by unions to bargain for higher wages, by hospital, school boards, manufacturers, builders, transportation companies, and by consumers in general. A common misconception is that time series data originate from the direct and straightforward compilations of survey data, censuses, and administrative records. On the contrary, before publication time series are subject to statistical adjustments intended to facilitate analysis, increase efficiency, reduce bias, replace missing values, correct errors, and satisfy cross-sectional additivity constraints. Some of the most common adjustments are benchmarking, interpolation, temporal distribution, calendarization, and reconciliation. This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book. This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view. The book will promote better procedures by large producers of time series, e.g. statistical agencies and central banks. Furthermore, knowing what adjustments are made to the data and what technique is used and how they affect the trend, the business cycles and seasonality of the series, will enable users to perform better modeling, prediction, analysis and planning. This book will prove useful to graduate students and final year undergraduate students of time series and econometrics, as well as researchers and practitioners in government institutions and business. From the reviews: 'It is an excellent reference book for people working in this area.' B. Abraham for Short Book Reviews of the ISI, December 2006

Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
Afficher sur iTunes
  • 79,99 €
  • Disponible sur iPhone, iPad, iPod touch et sur Mac.
  • Catégorie : Économie
  • Sortie : 23 sept. 2006
  • Éditeur : Springer New York
  • Pages : 424
  • Langue : Anglais
  • Configuration requise : Pour consulter ce livre, vous devez avoir un appareil iOS muni d’iBooks 1.3.1 (ou une version ultérieure) et d’iOS 4.3.3 (ou une version ultérieure) ; ou un Mac avec iBooks 1.0 (ou une version ultérieure) et OS X 10.9 (ou une version ultérieure).


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