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Seasonal Adjustment with the X-11 Method

'Lecture Notes in Statistics'. Softcover reprint of the o…
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Titel: Seasonal Adjustment with the X-11 Method
Autor/en: Dominique Ladiray, Benoit Quenneville

ISBN: 0387951717
EAN: 9780387951713
'Lecture Notes in Statistics'.
Softcover reprint of the original 1st ed. 2001.
Book.
Sprache: Englisch.
Springer New York

10. Januar 2001 - kartoniert - 256 Seiten

The most widely used statistical method in seasonal adjustment is without doubt that implemented in the X-11 Variant of the Census Method II Seasonal Adjustment Program. Developed at the US Bureau of the Census in the 1950's and 1960's, this computer program has undergone numerous modifications and improvements, leading especially to the X-11-ARIMA software packages in 1975 and 1988 and X-12-ARIMA, the first beta version of which is dated 1998. While these software packages integrate, to varying degrees, parametric methods, and especially the ARIMA models popularized by Box and Jenkins, they remain in essence very close to the initial X-11 method, and it is this "core" that Seasonal Adjustment with the X-11 Method focuses on. With a Preface by Allan Young, the authors document the seasonal adjustment method implemented in the X-11 based software. It will be an important reference for government agencies, macroeconomists, and other serious users of economic data. After some historical notes, the authors outline the X-11 methodology. One chapter is devoted to the study of moving averages with an emphasis on those used by X-11. Readers will also find a complete example of seasonal adjustment, and have a detailed picture of all the calculations.
1 Brief History of Seasonal Adjustment.- 2 Outline of the X-11 Method.- 2.1 Components and Decomposition Models.- 2.2 Moving Averages.- 2.3 A Simple Seasonal Adjustment Algorithm.- 2.4 The Basic Algorithm of the X-11 Method.- 2.5 Extreme Observations and Calendar Effects.- 2.6 The Iterative Principle of X-11.- 2.6.1 Part A: Pre-Adjustments.- 2.6.2 Part B: First Automatic Correction of the Series.- 2.6.3 Part C: Second Automatic Correction of the Series.- 2.6.4 Part D: Seasonal Adjustment.- 2.6.5 Parts E, F and G: Statistics and Charts.- 2.7 From Census X-11 to X-11-ARIMA and X-12-ARIMA.- 3 Moving Averages.- 3.1 Some Definitions and a Little Theory.- 3.1.1 Definitions and Example.- 3.1.2 Gain and Phase Shift Functions.- 3.1.3 Trend Preservation.- 3.1.4 Elimination of Seasonality.- 3.1.5 Reduction of the Irregular Component.- 3.1.6 An Example of Construction of a Moving Average.- 3.2 The Symmetric Moving Averages Used in X-11.- 3.2.1 Composite Simple Moving Average.- 3.2.2 Henderson Moving Averages.- 3.3 Musgrave Asymmetric Moving Averages.- 3.3.1 Musgrave Asymmetric Moving Averages Associated with Henderson Symmetric Moving Averages.- 3.3.2 Comment About Musgrave Moving Averages.- 3.3.3 Asymmetric Moving Averages Associated With Composite Moving Averages.- 3.4 The X-11 Moving Average Filter.- 4 The Various Tables.- 4.1 B: Preliminary Estimation of Extreme Values and Calendar Effects.- 4.1.1 B1: Raw Series Adjusted a priori.- 4.1.2 B2: Trend-Cycle.- 4.1.3 B3: Unmodified Seasonal-Irregular.- 4.1.4 B4: Replacement Values for Extreme SI Values.- 4.1.5 B5: Seasonal Component.- 4.1.6 B6: Seasonally Adjusted Series.- 4.1.7 B7: Trend-Cycle.- 4.1.8 B8: Unmodified SI Component.- 4.1.9 B9: Replacement Values for Extreme SI Values.- 4.1.10 B10: Seasonal Component.- 4.1.11 B11 : Seasonlly Adjusted Series.- 4.1.12 B13: Irregular Component.- 4.1.13 The Trading-Day Component.- 4.1.14 B14: Irregular Values Excluded from the TD Regression.- 4.1.15 B15: Preliminary TD Regression.- 4.1.16 B16: Regression-D erived TD Adjustment Factors.- 4.1.17 B17: Preliminary Weights for the Irregular.- 4.1.18 B18: Combined TD Factors.- 4.1.19 B19: Raw Series Corrected for TD Effects.- 4.1.20 B20: Adjustment Values for Extreme Irregulars.- 4.2 C: Final Estimation of Extreme Values and Calendar Effects.- 4.2.1 C1: Modified Raw Series.- 4.2.2 C2: Trend-Cycle.- 4.2.3 C4: Modified SI.- 4.2.4 C5: Seasonal Component.- 4.2.5 C6: Seasonally Adjusted Series.- 4.2.6 C7: Trend-Cycle.- 4.2.7 C9: SI Component.- 4.2.8 C10: Seasonal Component.- 4.2.9 Cll: Seasonally Adjusted Series.- 4.2.10 C13: Irregular Component.- 4.2.11 C14: Irregulars Excluded from the TD Regression.- 4.2.12 C15: Final TD Regression.- 4.2.13 C16: Regression-Derived TD Adjustment Factors.- 4.2.14 C17: Final Weights for the Irregular.- 4.2.15 C18: Combined TD Factorstt.- 4.2.16 C19: Raw Series Corrected for TD Effects.- 4.2.17 C20: Adjustment Values for Extreme Irregulars.- 4.3 D: Final Estimation of the Different Componentst.- 4.3.1 D1: Modi fied Raw Series.- 4.3.2 D2: Trend-Cycle.- 4.3.3 D4: Modified SI.- 4.3.4 D5: Seasonal Componentt.- 4.3.5 D6: Seasonally Adjusted Seriestt.- 4.3.6 D7: Trend-Cycle.- 4.3.7 D8: Unmodified SI Component.- 4.3.8 D9: Replacement Values for Extreme SI Values.- 4.3.9 D9A: Moving Seasonality Ratios.- 4.3.10 Dl0: Final Seasonal Factors.- 4.3.11 D11 : Final Seasonally Adjusted Series 150.- 4.3.12 D11A: Final Seasonally Adjusted Series with Revised Annual Totals.- 4.3.13 D12: Final Trend-Cycle.- 4.3.14 D13: Final Irregular Component.- 4.3.15 D16: Seasonal and Calendar Effects.- 4.3.16 D18: Combined Calendar Effects Factors.- 4.4 E: Components Modified for Large Extreme Values.- 4.4.1 E1: Raw Series Modified for Large Extreme Values.- 4.4.2 E2: SA Series Modified for Large Extreme Values.- 4.4.3 E3: Final Irregular Component Adjusted for Large Extreme Values.- 4.4.4 E4: Comparing the Annual Totals of Raw and SA Series.- 4.4.5 E5: Changes in the Raw Series.- 4.4.6 E6: Changes in the Final SA Series.- 4.4.7 E7: Changes in the Final Trend-Cycle.- 4.4.8 E11: Robust Estimation of the Final SA Series.- 4.5 F: Seasonal Adjustment Quality Measures.- 4.5.1 F1: Smoothing the SA Series Using an MCD MA.- 4.5.2 F2A: Changes, in Absolute Value, of the Principal Components.- 4.5.3 F2B: Relative Contribution of Components to Changes in the Raw Series.- 4.5.4 F2C: Averages and Standard Deviations of Changes as a Function of the Time Lag.- 4.5.5 F2D: Average Duration of Run.- 4.5.6 F2E: Calculation of the MCD Ratio.- 4.5.7 F2F: Relative Contribution of Components to the Variance of the Stationary Part of the Original Series.- 4.5.8 F2G: Autocorrelations of the Irregular Component.- 4.5.9 F2H: % MathType!MTEF!2!1!+-
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$$ Ratios.- 4.5.10 F2I: Tests for the Presence of Seasonality.- 4.5.11 F3: Monitoring and Quality Assessment Statistics.- 5 Modelling of the Easter Effect.- 5.1 The Easter Holiday.- 5.1.1 A Brief History.- 5.1.2 Calculation of the Dates of Easter.- 5.1.3 Easter and Seasonal Adjustment.- 5.2 The X-11-ARIMA Models.- 5.2.1 The Immediate Impact Model.- 5.2.2 The Corrected Immediate Impact Model.- 5.2.3 The Gradual Impact Model.- 5.3 The X-12-ARIMA Models.- 5.3.1 The Bateman-Mayes Model.- 5.3.2 The Sceaster Model.- 5.3.3 The Easter Model.- References.

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