Seasonal Adjustment with the X-11 Method

ISBN-13: 9780387951713 / Angielski / Miękka / 2001 / 256 str.

Dominique Ladiray; Benoit Quenneville

Opis

The authors, Dominique Ladiray and Benoit Quenneville, provide a unique and comprehensive r view of the X-11 Method of seasonal adjustment. They review the original X-11 Method developed at the US Bureau of the Census in the mid-1960's, the X-ll core of the X-ll-ARTMA Method developed at Statistics Canada in the 1970's, and the X-11 module in the X- 12-ARTMA Method developed more recently at the Bureau of the Census. The review will prove extremely useful to anyone working in the field of seasonal adjustment who wants to understand the X-11 Method and how it fits into the broader picture of seasonal adjustment. What the authors designate as the X-11 Method was originally desig- nated the X-11 Variant of the Census Method IT Seasonal Adjustment Program. It was the culmination of the pioneering work undertaken at the Bureau of the Census by Julius Shiskin in the 1950's. Shiskin introduced the Census Method T Seasonal Adjustment Program in 1954 and soon followed it with the introduction of Method TT in 1957.

Spis treści

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!+- % feaagaart1ev2aaatCvAUfKttLearuqr1ngBPrgarmWu51MyVXguY9 % gCGievaerbd9wDYLwzYbWexLMBbXgBcf2CPn2qVrwzqf2zLnharyav % P1wzZbItLDhis9wBH5garqqtubsr4rNCHbGeaGqiVu0Je9sqqrpepC % 0xbbL8F4rqqrFfpeea0xe9Lq-Jc9vqaqpepm0xbba9pwe9Q8fs0-yq % 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The Bateman-Mayes Model.- 5.3.2 The Sceaster Model.- 5.3.3 The Easter Model.- References.