Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series

Modern economies rely on time series at all levels of activity. Time series are used by decision makers to plan for a better future. Governments use them to promote prosperity, and central banks apply them to control inflation. Before publication time series are subject to statistical adjustments and this is the first book to systematically deal with these time series data transformations.

Regression-based models 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 is followed throughout the book. This publication will promote better procedures by large producers of time series including statistical agencies and central banks.

First statistical book to systematically deal with these time series data transformations

Contenu
The Components of Time Series.- The Cholette-Dagum Regression-Based Benchmarking Method The Additive Model.- Covariance Matrices for Benchmarking and Reconciliation Methods.- The Cholette-Dagum Regression-Based Benchmarking Method - The Multiplicative Model.- The Denton Method and its Variants.- Temporal Distribution, Interpolation and Extrapolation.- Signal Extraction and Benchmarking.- Calendarization.- A Unified Regression-Based Framework for Signal Extraction, Benchmarking and Interpolation.- Reconciliation and Balancing Systems of Time Series.- Reconciling One-Way Classified Systems of Time Series.- Reconciling the Marginal Totals of Two-Way Classified Systems of Series.- Reconciling Two-Way Classifed Systems of Series.