Economic Time Series: Modeling and Seasonality

William R. Bell, Scott H. Holan, Tucker S. McElroy

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March 19, 2012 by Chapman and Hall/CRC
Reference - 554 Pages - 146 B/W Illustrations
ISBN 9781439846575 - CAT# K12089

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Features

    • Presents contributions from some of the leading researchers in the field from both academia and government statistical agencies
    • Includes new methodological developments and innovative empirical analyses
    • Focuses on applied problems of seasonal economic time series, such as periodic behavior, consequences of model misspecification, sampling error in time series data, diagnostics for seasonal adjustment, and outliers

    Summary

    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 series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies.

    For easier perusal and absorption, the contents have been grouped into seven topical sections:

    • Section I deals with periodic modeling of time series, introducing, applying, and comparing various seasonally periodic models
    • Section II examines the estimation of time series components when models for series are misspecified in some sense, and the broader implications this has for seasonal adjustment and business cycle estimation
    • Section III examines the quantification of error in X-11 seasonal adjustments, with comparisons to error in model-based seasonal adjustments
    • Section IV discusses some practical problems that arise in seasonal adjustment: developing asymmetric trend-cycle filters, dealing with both temporal and contemporaneous benchmark constraints, detecting trading-day effects in monthly and quarterly time series, and using diagnostics in conjunction with model-based seasonal adjustment
    • Section V explores outlier detection and the modeling of time series containing extreme values, developing new procedures and extending previous work
    • Section VI examines some alternative models and inference procedures for analysis of seasonal economic time series
    • Section VII deals with aspects of modeling, estimation, and forecasting for nonseasonal economic time series

    By presenting new methodological developments as well as pertinent empirical analyses and reviews of established methods, the book provides much that is stimulating and practically useful for the serious researcher and analyst of economic time series.