The X12 Procedure |
X11 Statement |
The X11 statement is an optional statement for invoking seasonal adjustment by an enhanced version of the methodology of the Census Bureau X-11 and X-11Q programs. You can control the type of seasonal adjustment decomposition calculated with the MODE= option. The output includes the final tables and diagnostics for the X-11 seasonal adjustment method listed in Table 32.5. Tables C20, D1, and D7 are not displayed by default; you can display these tables by using the TABLES statement.
Table Name |
Description |
B1 |
original series, adjusted for prior effects and forecast extended |
C17 |
final weights for the irregular component |
C20 |
final extreme value adjustment factors |
D1 |
modified original data, D iteration |
D7 |
preliminary trend cycle, D iteration |
D8 |
final unmodified SI ratios (differences) |
D8A |
F tests for stable and moving seasonality, D8 |
D9 |
final replacement values for extreme SI ratios (differences), D iteration |
D9A |
moving seasonality ratios for each period |
D10 |
final seasonal factors |
D10B |
seasonal factors, adjusted for user-defined seasonal |
D10D |
final seasonal difference |
D11 |
final seasonally adjusted series |
D11A |
final seasonally adjusted series with forced yearly totals |
D11R |
rounded final seasonally adjusted series (with forced yearly totals) |
D12 |
final trend cycle |
D13 |
final irregular component |
D16 |
combined seasonal and trading day factors |
D16B |
final adjustment differences |
D18 |
combined calendar adjustment factors |
E4 |
ratio of yearly totals of original and seasonally adjusted series |
E5 |
percent changes (differences) in original series |
E6 |
percent changes (differences) in seasonally adjusted series |
E6A |
percent changes (differences) in seasonally adjusted series with forced yearly totals (D11.A) |
E6R |
percent changes (differences) in rounded seasonally adjusted series (D11.R) |
E7 |
percent changes (differences) in final trend component series |
F2A–F2I |
X11 diagnostic summary |
F3 |
monitoring and quality assessment statistics |
F4 |
day of the week trading day component factors |
G |
spectral plots |
For more details about the X-11 seasonal adjustment diagnostics, see Shiskin, Young, and Musgrave (1967), Lothian and Morry (1978a), and Ladiray and Quenneville (2001).
The following options can appear in the X11 statement.
determines the mode of the seasonal adjustment decomposition to be performed. There are four choices: multiplicative (MODE=MULT), additive (MODE=ADD), pseudo-additive (MODE=PSEUDOADD), and log-additive (MODE=LOGADD) decomposition. If this option is omitted, the procedure performs multiplicative adjustments. Table 32.6 shows the values of the MODE= option and the corresponding models for the original (O) and the seasonally adjusted (SA) series.
Value of Mode Option |
Name |
Model for |
Model for |
MULT |
multiplicative |
|
|
ADD |
additive |
|
|
PSEUDOADD |
pseudo-additive |
|
|
LOGADD |
log-additive |
|
|
determines whether forecasts are included in certain tables sent to the output data set. If OUTFORECAST is specified, then forecast values are included in the output data set for tables A6, A7, A8, A9, A10, B1, D10, D10B, D10D, D16, D16B, and D18. The default is not to include forecasts.
specifies which seasonal moving average (also called seasonal "filter") be used to estimate the seasonal factors. These seasonal moving averages are moving averages, meaning that an -term simple average is taken of a sequence of consecutive -term simple averages. X11DEFAULT is the method used by the U.S. Census Bureau’s X-11-ARIMA program. The default for PROC X12 is SEASONALMA=MSR, which is the methodology of Statistic Canada’s X-11-ARIMA/88 program.
Table 32.7 describes the seasonal filter options available for the entire series:
Filter Name |
Description of Filter |
S3X1 |
a moving average |
S3X3 |
a moving average |
S3X5 |
a moving average |
S3X9 |
a moving average |
S3X15 |
a moving average |
STABLE |
stable seasonal filter. A single seasonal factor for each |
calendar month or quarter is generated by calculating the simple |
|
average of all the values for each month or quarter (taken after |
|
detrending and outlier adjustment). |
|
X11DEFAULT |
a moving average is used to calculate the |
initial seasonal factors in each iteration, and a moving |
|
average to calculate the final seasonal factors |
|
MSR |
filter chosen automatically by using the moving seasonality |
ratio of X-11-ARIMA/88 (Dagum; 1988) |
specifies which Henderson moving average be used to estimate the final trend cycle. Any odd number greater than one and less than or equal to 101 can be specified. Example: TRENDMA=23. If no selection is made, the program selects a trend moving average based on statistical characteristics of the data. For monthly series, a 9-, 13-, or 23-term Henderson moving average is selected. For quarterly series, the program chooses either a 5- or a 7-term Henderson moving average.
lists the types of prior adjustment factors, obtained from the regression and outlier statements, that are to be removed from the final seasonally adjusted series. Additive outliers (FINAL=AO), level change and ramp outliers (FINAL=LS), and temporary change (FINAL=TC) can be removed. If this option is not specified, the final seasonally adjusted series contains these effects.
specifies that the seasonally adjusted series be modified to (a) force the yearly totals of the seasonally adjusted series and the original series to be the same (FORCE=TOTALS), (b) adjust the seasonally adjusted values for each calendar year so that the sum of the rounded seasonally adjusted series for any year equals the rounded annual total (FORCE=ROUND), or (c) first force the yearly totals, then round the adjusted series (FORCE=BOTH). When FORCE=TOTALS, the differences between the annual totals is distributed over the seasonally adjusted values in a way that approximately preserves the month-to-month (or quarter-to-quarter) movements of the original series. For more details, see Huot (1975) and Cholette (1979). This forcing procedure is not recommended if the seasonal pattern is changing or if trading day adjustment is performed. Forcing the seasonally adjusted totals to be the same as the original series annual totals can degrade the quality of the seasonal adjustment, especially when the seasonal pattern is undergoing change. It is not natural if trading day adjustment is performed because the aggregate trading day effect over a year is variable and moderately different from zero.
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