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Current Employment Statistics - CES (National)

CES Seasonal Adjustment Technical Notes

The CES program employs a concurrent seasonal adjustment methodology to seasonally adjust its national estimates of employment, hours, and earnings. Under concurrent methodology, new seasonal factors are calculated each month using all relevant data up to and including the current month period. Once a year, BLS seasonally adjusts CES series again, replacing the most recent 5 years of historical estimates with newly seasonally adjusted estimates. This technical note describes the application, files, and process of seasonally adjusting CES estimates of employment, hours, and earnings, both monthly and for the annual re-adjustment, using the U.S. Census Bureau's X-13ARIMA-SEATS application. For more information on CES seasonal adjustment methodology, see Seasonal adjustment under Calculation in the CES Handbook of Methods.

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Seasonal adjustment and X-13ARIMA-SEATS

The CES program uses X-13ARIMA-SEATS software developed by the U.S. Census Bureau to seasonally adjust monthly estimates. For more information about X-13ARIMA-SEATS please visit the U.S. Census Bureau website. The following files are available from the Census website:

  • Program files for the latest PC version of X-13ARIMA-SEATS
  • Program files for the latest UNIX workstation version of X-13ARIMA-SEATS
  • Program files for X-13-Graph, a companion graphics package
  • Installation instructions
  • Reference manual

The remainder of this section describes how CES employs X-13ARIMA-SEATS for seasonal adjustment purposes. Specifically, it describes the input files used in the CES program's implementation and commands used to invoke the software. This is not a substitute for formal X-13ARIMA-SEATS training. There are other uses and features of X-13ARIMA-SEATS that are not discussed in this section. The U.S. Census Bureau offers more intensive training for X-13ARIMA-SEATS and seasonal adjustment. Contact the Census Bureau or visit their website for more details.

CES seasonal adjustment input files

All controllable variables remain fixed during the year. For example, the ARIMA model, outliers, transformation specification, and historical data are held constant, and the same calendar treatments are used throughout the year for concurrent seasonal adjustment. Once a year, as part of the annual CES benchmark procedure, all seasonal adjustment specifications are reviewed for each series. Any changes are implemented and kept constant until the next annual benchmark. Also during the annual benchmark, estimates for the 5 most recent years are re-seasonally adjusted using the new specifications. After 5 years of revisions, seasonally adjusted data are generally not updated again. However, if a series is reconstructed further back than 5 years, the entire time span of the reconstruction is seasonally adjusted again.

The CES program uses the following input files when seasonally adjusting estimates:

  • Specification file
  • Input data file
  • Prior-adjustment file
  • User-defined regression variables (dummy variables) file
  • Metafile
  • Recent outliers

More details on each input follow.

Specification file

An input specification file, or a "spec" file, is a text file used to specify program operations. The spec file is composed of functional units called specifications (or "specs"). Each spec unit comprising the spec file controls the options for a specific function. There are 15 different specs that can be used in a spec file; however, the CES program's implementation typically employs only 8 specs for most series and 9 specs for indirectly seasonally adjusted series. These specs are the following:

  • SERIES spec — this specifies the location and format of the data
  • TRANSFORM spec — this specifies a data transformation
  • REGRESSION spec — this specifies any regression components
  • ARIMA spec — this specifies the ARIMA model to be used
  • ESTIMATE spec — this estimates the regARIMA model
  • FORECAST spec — this generates forecasts of seasonal factors
  • OUTLIER spec — this specifies automatic outlier detection
  • X11 spec — this generates and controls the seasonal adjustment process
  • COMPOSITE spec — this is a special spec used only during indirect seasonal adjustment

Each spec used by the CES program is covered in greater detail at the end of this section in Anatomy of a Spec File.

In the CES program, each seasonally adjusted employment series has its own spec file ending in a ".spc" file extension. The ".spc" extension is not recognizable by all operating systems and usually needs to be opened with a text editor such as TextPad, Wordpad, or Notepad. Also, it is important to remember that when running X-13ARIMA-SEATS in DOS, the name of the spec file must be 8 characters or less. This is a limitation of DOS, not X-13ARIMA-SEATS. All of the spec files currently used in production can be downloaded from the CES seasonal adjustment webpage.

Input data file

The input data file consists of not seasonally adjusted CES estimates for all series that have a corresponding seasonally adjusted series and is referred to in the SERIES spec of the spec file. The CES implementation reads input data from a text file in "free format" style. In the free-format style, data are delimited with either tabs or spaces, and only the input data are included—dates and other descriptive information are excluded. Instead, information describing the data is specified in the SERIES spec using the START and PERIOD arguments. The full path and name of the input data file is specified using the FILE argument (see figure 1).

Figure 1. Input data file specifications

Figure 1. Input Data File Specifications

To Table of Figures

CES data can be found on the CES National Databases webpage. However, in some cases, not seasonally adjusted data extracted from the BLS website will differ from what the CES program actually uses in seasonal adjustment. In particular, data extracted from the BLS website will reflect any strikes or other prior adjustments that have taken place. Before running seasonal adjustment, the CES program will reverse these effects so that they will not be considered when calculating the seasonal factors. Also, the CES program uses unrounded data when running seasonal adjustment, while published data on the BLS website are rounded.

Prior adjustment file

As mentioned in the previous section, in some cases the CES program will modify the not seasonally adjusted estimates (input data) before running X-13ARIMA-SEATS. This is done to ensure that nonseasonal events such as strikes are not included in the calculation of the seasonal factors. Once the seasonal factors are calculated, they are applied to the not seasonally adjusted data used as inputs. Then the prior adjustments that were removed before running X-13ARIMA-SEATS are incorporated to create the seasonally adjusted estimates. To read more about the impact of strikes on CES data, visit the CES strike report webpage.

The latest prior adjustment file used in the seasonal adjustment of CES data can be downloaded from the CES seasonal adjustment webpage. The prior adjustment file is updated annually to reflect the series structure adopted with the benchmark, and it is updated monthly with each release of CES national estimates to include strike data. In the example shown below in figure 2, the first column contains the 14-digit CES NAICS tabcode. This tabcode identifies the series by an 8-digit industry code, followed by three zeros used as placeholders, a 2-digit data type code, and a single digit indicating seasonal adjustment (3 for not seasonally adjusted, 5 for seasonally adjusted). The tabcode structure is similar to the CES series ID structure, described on the CES NAICS webpage. The second column contains the year, and the next 12 columns represent the months of the year in sequential order (January through December). The file contains both positive and negative numbers. The positive numbers reflect a strike and are added to the not seasonally adjusted data before running X-13ARIMA-SEATS. The negative numbers reflect the buildup of employment associated with the decennial census and are added to the not seasonally adjusted data before calculating the seasonal factors.

Figure 2. Prior adjustment file format(1)
Figure 2. Prior adjustment file format

Footnotes
(1) The prior adjustment file contains unrounded data and must be adjusted to the thousands rounded to one decimal place to be comparable to CES employment estimates.

To Table of Figures

User-defined regression variable file

The CES program's current implementation of seasonal adjustment controls for several non-economic calendar related fluctuations in the estimates (described in the CES Handbook of Methods in Calculations under Seasonal adjustment. This is done with the inclusion of user-defined regression (or "dummy") variables. The dummy variables are defined in the REGRESSION spec of the spec file. The dummy files vary depending upon the type of calendar event being treated. Table 1 lists the dummy files used and the calendar event(s) they are used to treat.

Table 1. Dummy files with calendar treatment
Dummy File Calendar Event Treated

Fdum8606.dat

4 vs. 5 week effect 

Fdumpc96.dat

4 vs. 5 week effect plus a special adjustment for the presence/absence of poll workers in local government 

Fdumpcw6.dat 

4 vs. 5 week effect plus a special adjustment for the presence/absence of poll workers in local government (only applies to women employee series)

Fdumw96.dat

4 vs. 5 week effect plus a special adjustment for the presence/absence of an annual increase in postal employment in December (only applies to U.S. Postal Services, 90-919120)

Fdumel06.dat

Good Friday (Easter)/Labor Day adjustment

Fdumel96.dat

4 vs. 5 week effect plus Good Friday (Easter)/Labor Day adjustment

Dumlp06.dat

10/11 day effect

Dumlpel6.dat

10/11 day effect plus Good Friday (Easter)/Labor Day adjustment

To Table of Figures

The dummy values are usually 1 and 0, with weights assigned so that the effect over a 10-year period sums to zero. The latest user-defined regression files used in the seasonal adjustment of CES data can be downloaded from the CES seasonal adjustment webpage.

Metafile

The metafile is a text file ending in a ".mta" file extension and is used when running X-13ARIMA-SEATS on more than one series. It is essentially a list of the complete path and filename—without the extension—of all of the input spec files. Only one spec file is listed per row. As with the individual spec files, it is important to remember that when running X-13ARIMA-SEATS in DOS, the name of the metafile must be 8 characters or less.

Recent outliers

The latest outliers used in the seasonal adjustment of CES data can be downloaded from the CES seasonal adjustment webpage in the ces.spec.others.zip file. Outliers are any data point that falls outside of the normal monthly values for CES data. The list of these outliers is updated monthly with each release of CES national estimates as an excel table called outliers.xlsx that lists the month, year, and industry code of recent outliers manually identified during analyst review. The file contains outliers from the November following the most recent benchmark to the present month.

Until the 2021 benchmark, BLS included only point outliers (also known as additive outliers, or AO) in its annual seasonal adjustment processing. Point outliers only affect the month in which they occur and do not have a persistent influence over subsequent months. Only using AOs allowed for more control over outliers from the end of the input series, in the most recent year of data. However, research into the effects of the COVID-19 pandemic on seasonal patterns has resulted in changes to how BLS will treat outliers in CES seasonal adjustment from January 2022 forward.

BLS will allow other types of outliers, known as temporary change (TC) and level shift (LS) outliers, to be included in seasonal adjustment of series. Point outliers indicate that a shock only affected that particular point in time. Temporary change outliers show a shock to one month of data followed by an effect on subsequent months that diminishes over time. Level shift outliers show a shock that interrupts a normal seasonal pattern that is then continued on the new post-shock level. Any shock at the end of a time series must be an AO because TC and LS outliers can only be identified after enough time has passed to recognize either a diminishing effect (for a TC) or a continuation of seasonal pattern at the new level (for an LS).

A seasonal adjustment run selecting only AOs is run initially. The other two outlier types, in addition to the AO outliers, are automatically chosen by X13-ARIMA-SEATS and used in a second seasonal adjustment run. Both the AO-only and additional outlier runs are manually reviewed by CES analysts for each basic level series, and the seasonally adjusted series with the best fit is chosen. The outliers.xlsx file will contain a full account of AO, TC, and LS outliers chosen for each month.

Running X-13 on a single series

Use the following command at the DOS prompt when running X-13ARIMA-SEATS on a single series:

{path1\}x13as {path2\}spec file name -options

where {path1\}
= path of the X-13ARIMA-SEATS program
x13as
= command informing X-13 program to execute
{path2\}
= path of the spec file
spec file name
= name of the input spec file you want to adjust (without the extension)
options
= see X-13 manual for list of options

Example: At the DOS prompt, type:

c:\x13as\x13as c:\x13\seasadj\AE113310 -w

(where AE113310.spc is the series you want to adjust)

Running X-13 on multiple series

Use the following command at the DOS prompt when running X-13ARIMA-SEATS on more than one series:

{path1\}x13as -m {path2\}metafile name -options

where {path1\}
= path of the X-13ARIMA-SEATS program
x13as
= command informing X-13 program to execute
-m
= flag that informs X-13 that the subsequent named file is a metafile
{path2\}
= path of the metafile
metafile name
= name of the metafile (without the extension) containing the input spec files
options
= see X-13 manual for list of options

Example: At the DOS prompt, type:

c:\x13as\x13as -m c:\x13\seasadj\pubAE -w

(where pubAE.mta is the metafile you are using)

Output from X-13ARIMA-SEATS

When X-13ARIMA-SEATS is run, several output files are generated by default. The output files are saved in the same location as the input specification files.

  • Main output file (*.out)
  • Error output file (*.err)
  • Log output file (*.log)

More details follow on each of the output files.

Main output file (*.out)

The X-13ARIMA-SEATS output is written to a text file ending in a ".out" extension. Output from the CES implementation contains many different tables and statistics, including:

  • Table displaying the original, not seasonally adjusted series
  • Table displaying the final seasonally adjusted series
  • Table displaying the final seasonal factors
  • Statistics related to model selection
  • Statistics related to outlier detection
  • A summary of seasonal adjustment diagnostics
  • Quality control statistics

Individual specs in the spec file control their contribution to this output using optional PRINT arguments. For example, within the X11 spec, BRIEF specifies that only certain tables or plots are printed, while the minus sign in front of a name (such as -SPECSA or -SPECIRR) means that particular table or plot should be suppressed from the output. In this example, without the options -SPECSA and -SPECIRR, both of the plots would be printed by default under the BRIEF option.

Figure 3. The PRINT argument in the X11 spec

Figure 3. The PRINT Argument in the X11 Spec

To Table of Figures

It is important to remember that every time X-13ARIMA-SEATS is run on a particular series, the *.out file is overwritten, unless an alternate name or directory is specified.

Error output file (*.err)

Input errors are written to a text file ending in an ".err" extension. If the error is fatal, ERROR: will be displayed before the error message. If the error is not fatal, WARNING: will be printed before the message. Nonfatal errors (or warnings) will not stop the program, but they should be an alert to use caution and to check input and output carefully.

It is important to remember that, as is the case with all output files, every time X-13ARIMA-SEATS is run on a particular series, the *.err file is overwritten, unless an alternate name or directory is specified.

Log output file (*.log)

A summary of modeling and seasonal adjustment diagnostics are written to a text file ending in a ".log" extension. Individual specs in the specification file control their contribution to this output using optional SAVELOG arguments. When X-13ARIMA-SEATS is run on an individual spec file, the log file is stored with the same name and directory as the spec file. However, when X-13 is run using a metafile, the log file is stored with the same name and directory as the metafile. As is with all output files, every time X-13ARIMA-SEATS is run, the *.log file is overwritten unless an alternate name or directory is specified.

Other output files

Other output files are generated as specified in the spec file using the SAVE argument. In the CES program's implementation, the following additional output files are generated:

  • *.a1 – This file contains the not seasonally adjusted data with associated dates and is specified in the SERIES spec
  • *.ao – This file contains outlier factors with associated dates and is specified in the REGRESSION spec
  • *.d10 – This file contains final seasonal factors with associated dates and is specified in the X11 spec
  • *.d11 – This file contains final seasonally adjusted data with associated dates and is specified in the X11 spec
  • *.d16 – This file contains combined seasonal and trading day factors with associated dates and is specified in the X11 spec
  • *.td – This file contains final trading day factors with associated dates and is specified in the REGRESSION spec

Indirect seasonal adjustment

The CES program generally seasonally adjusts published series directly at the 3-digit NAICS level and aggregates to the higher levels. However, there are some exceptions to this rule. In a few of the AE series, the CES program will seasonally adjust at a level lower than the 3-digit NAICS level. In these instances, the CES program seasonally adjusts the 3-digit series indirectly, meaning all of the component (lower level) series are seasonally adjusted directly and aggregated up to the composite (3-digit) level. Indirect seasonal adjustment is performed on these series because some of the individual component series that aggregate to the composite series exhibit different seasonal patterns that may be masked if the data are seasonally adjusted directly at the aggregate level.

The spec file for the composite series differs somewhat from normal CES implementation. The most significant difference is at the beginning of the spec file, where the SERIES spec is replaced with the COMPOSITE spec. Running X-13 employing the COMPOSITE spec produces an indirect seasonal adjustment of the composite series as well as a direct adjustment. Output from the indirect adjustment is saved under nonstandard file extensions.

  • Aggregated not seasonally adjusted data with associated dates are saved in a text file with the extension *.cms (instead of *.a1 under direct seasonal adjustment)
  • Final indirect (aggregated) seasonally adjusted data with associated dates are saved in a text file with the extension *.isa (instead of *.d11 under direct seasonal adjustment)
  • Final seasonal factors for aggregated series with associated dates are saved in a text file with the extension *.isf (instead of *.d16 under direct seasonal adjustment)

The COMPOSITE spec is covered in greater detail at the end of this section in Anatomy of a Spec File. Seasonal adjustment of the component series that go into a composite series is run using X-13ARIMA-SEATS in the same way as a standard seasonally adjusted series but is then summed to the composite level. A metafile listing the file locations and names (without the .spc extension) of the composite series followed by all of its component series is used to seasonally adjust a composite series.

Industries that are currently indirectly seasonally adjusted and their component series are listed in Indirectly seasonally adjusted CES series in the CES Handbook of Methods. For any given series, not all of the component series are published at first closing. Some series are published during a later release. In the linked table, component series published with the second preliminary data release are footnoted.

Anatomy of a spec file

For published series, the CES program generally seasonally adjusts at the 3-digit NAICS level and aggregates to the higher levels. A small number of series are independently seasonally adjusted at a higher level of detail, but these are not included in the aggregation of seasonally adjusted data. One of the main inputs to the seasonal adjustment process is a unique file called a spec file. The spec file contains a set of specs that give X-13ARIMA-SEATS various information about the data and the desired seasonal adjustment options and output. Each specification inside the spec file controls options for a specific function. For example, the SERIES spec contains specifications on the location and format of the data, while the X11 spec sets seasonal adjustment options such as seasonal adjustment transformation mode, output files to save, and diagnostic statistics to print.

Figure 4. CES seasonal adjustment spec file

Example of a Specifications File: text of a spec file with explanations of SERIES, TRANSFORM, REGRESSION, ARIMA, ESTIMATE, FORECAST, OUTLIER, and X11 specs. Further details about each spec are in the text below.

To Table of Figures

The spec file is free format, and blank spaces, tabs, and blank lines may be used as desired to make the spec file more readable. The order of the specification statements in the spec file (with one exception) and the order of the arguments within the braces of any spec do not matter. The only requirement is that the SERIES spec or COMPOSITE spec must be the first spec.

More detail on each spec used by CES follows.

1. SERIES spec

SERIES{

TITLE = "Logging"

START = 1993.01

PERIOD = 12

SAVE = A1

PRINT = BRIEF

NAME = '10113310 – AE'

FILE = 'c:\AE10113310.dat'}

The main function of the SERIES spec is to specify details about the input data series such as the name, format, and location of the data. The CES implementation employs seven options or arguments with the SERIES spec.

  • TITLE — A descriptive title for the series. In this example, the title is "Logging".
  • START — The start date of the time series being adjusted. In this example, the start date is January, 1993.
  • PERIOD — Seasonal period of the series. In this example, the period is 12 (which means monthly).
  • SAVE — Specifies output to be saved. In this example, the time series data with associated dates will be saved in an output file called AE10113310.A1.
  • PRINT — Specifies output to be printed. In this example, BRIEF specifies that only certain tables are printed.
  • NAME — The name of the time series. In this example, the name is "10113310 – AE".
  • FILE — The complete path and name of the file containing the time series data. In this example, the complete path and filename is "c:\AE10113310.dat".

2. TRANSFORM spec

TRANSFORM{FUNCTION = LOG}

The main function of the TRANSFORM spec is to transform or adjust the time series prior to estimating a regARIMA model. The CES implementation employs one argument with the TRANSFORM spec.

  • FUNCTION — Specifies the method to transform the time series. In this example, the transformation method is log transformation, which means X-13 will compute a multiplicative seasonal decomposition.

3. REGRESSION spec

REGRESSION{

VARIABLES = (AO2012.10 AO2020.04 AO2020.05 AO2020.06 AO2020.07 AO2020.10)

USER = (dum1 dum2 dum3 dum4 dum5 dum6 dum7 dum8 dum9 dum10 dum11)

START = 1986.01

FILE = 'c:\FDUM8606.dat'

USERTYPE = TD

SAVE = (TD AO TC LS) }

The main function of the REGRESSION spec is to specify the regression components of a regARIMA model. The CES implementation employs up to six options with the REGRESSION spec.

  • VARIABLES — Specifies any predefined regression variables to be included in the model. In the CES implementation, predetermined outliers are listed after the VARIABLES argument. In this example, predetermined outliers include AO2012.10 (October 2012), AO2020.04 (April 2020), AO2020.05 (May 2020), AO2020.06 (June 2020), AO2020.07 (July 2020), and AO2020.10 (October 2020).
  • USER — Specifies the names for any user-defined regression variables. CES defines regression variables to adjust for significant effects associated with calendar related events such as (1) the relative timing of the reference period of the survey and the Good Friday (Easter) and Labor Day holidays; (2) variations of 4 or 5 weeks between reference periods in any given pair of months, and; (3) differences in the number of working days in a pay period from month-to-month. In this example, the regression variables are named dum1, dum2, dum3, dum4, dum5, dum6, dum7, dum8, dum9, dum10, and dum11.
  • START — Specifies the start date for the data values for the user-defined regression variables. In this example, the start date is January, 1986.
  • FILE — The complete name of the file containing the data values for the user-defined regression variables, including the path. In this example, the filename, including the path, is "c:\FDUM8606.dat".
  • USERTYPE — Specifies a type of model-estimated regression effect to each user-defined regression variable. In this example, the type of model-estimated regression effect is defined as TD, or trading day.
  • SAVE — Specifies output to be saved. In this example, trading day factors with associated dates will be saved in an output file called AE10113310.TD, and point outlier factors with associated dates will be saved in an output file called AE10113310.AO. Had there been TC or LS outliers, they would have been saved in files called AE10113310.TC and AE10113310.LS.

Note: Not every option is used in every spec file. For example, if no predetermined outliers exist, then the VARIABLES argument will not be used. Likewise, if we are not treating a particular series for calendar effects, then the USER, START, FILE, and USERTYPE arguments will not be used.

4. ARIMA spec

ARIMA{MODEL = (1 1 0) (1 0 0)}

The main function of the ARIMA spec is to specify the ARIMA part of a regARIMA model. The CES implementation employs one option with the ARIMA spec.

  • MODEL — Specifies the actual ARIMA model to be used. In this example, the model is (1 1 0) (1 0 0).

5. ESTIMATE spec

ESTIMATE{MAXITER = 1000}

The main function of the ESTIMATE spec is to estimate the regARIMA model specified by the REGRESSION and ARIMA specs. The CES implementation employs one argument with the ESTIMATE spec.

  • MAXITER — Specifies the maximum number allowed of autoregressive moving average (ARMA) nonlinear iterations. ARMA is a time-series model that includes both autoregressive (AR) and moving average (MA) nonlinear components. In this example, the maximum number allowed of ARMA iterations is 1,000.

6. FORECAST spec

FORECAST{MAXLEAD = 24}

The main function of the FORECAST spec is to generate forecasts (and/or backcasts) for the time series model given in the SERIES spec using the estimated regARIMA model. The CES implementation employs one argument with the FORECAST spec.

  • MAXLEAD — Specifies the number of forecasts produced. In this example, the number of forecasts specified is 24 months.

7. OUTLIER spec

OUTLIER{

CRITICAL = 3.5

TYPES = (AO TC LS) }

The main function of the OUTLIER spec is to perform automatic detection of point outliers (AO), temporary change (TC) outliers, level shifts (LS), or any combination of the three. The CES implementation uses this spec to automatically detect all three types of outliers. CES employs two arguments with the OUTLIER spec.

  • CRITICAL — Specifies the value to which the absolute values of the outlier t-statistics are compared to detect outliers. In this example, the critical value is 3.5.
  • TYPES — Specifies the types of outliers to detect. The CES implementation uses the OUTLIER spec to automatically detect AO, TC, and LS outliers.

8. X11 spec

X11{

MODE = MULT

PRINT = (BRIEF -SPECSA -SPECIRR)

SAVE = (D10 D11 D16)

APPENDFCST = YES

FINAL = USER

SAVELOG = (Q Q2 M7 FB1 FD8 MSF) }

The function of the X11 spec is to control certain aspects of the seasonal adjustment process. For example, the CES implementation uses the X11 spec to control the type of seasonal adjustment decomposition calculated (mode). CES employs six arguments with the X11 spec.

  • MODE — Specifies the mode of the seasonal adjustment decomposition to be performed. There are four choices: multiplicative, additive, pseudo-additive, and log-additive. In the CES implementation, only the multiplicative or additive modes are employed. In this example, the mode specified is multiplicative (MULT).
  • PRINT — Specifies output to be printed. In this example, BRIEF specifies that only certain tables or plots are printed. The minus sign in front of a name means that particular table or plot should be suppressed. In this example, -SPECSA specifies that a spectral plot of differenced, seasonally adjusted series be suppressed, while -SPECIRR specifies that a spectral plot of outlier-modified irregular series be suppressed. Without these options, both plots would be printed under the BRIEF option by default.
  • SAVE — Specifies output to be saved. In this example, final seasonal factors with associated dates will be saved in an output file called AE10113310.D10; the final seasonally adjusted series with associated dates will be saved in an output file called AE10113310.D11; and combined seasonal and trading day factors with associated dates will be saved in an output file called AE10113310.D16.
  • APPENDFCST — Determines if forecasts of seasonal factors will be included in the X-13 output files and tables that were selected in the SAVE option. If APPENDFCST = yes, then forecasted seasonal factors will be stored. In this example, the APPENDFCST value is YES.
  • FINAL — Specifies the types of prior adjustment factors (obtained from the REGRESSION and OUTLIER specs) that are to be applied to the final seasonally adjusted series. In this example, FINAL = USER, which means that factors derived from user-defined regressors (or in this example, the dummy variables) are to be applied to the final seasonally adjusted series, removing significant effects associated with calendar related events.
  • SAVELOG — Specifies the diagnostic statistics to be printed to the log file. In this example, the following diagnostics will be printed:
    • Q, which is the overall index of the acceptability of the seasonal adjustment. The adjustment may be poor if Q > 1.
    • Q2, which is the Q-statistic computed without the M2 Quality Control Statistic. The M2 values can sometimes be misleading if the trend shows several changes of direction.
    • M7, which measures the moving seasonality relative to the stable seasonality found in the series. Any M > 1 indicates a source of potential problems for the adjustment procedure.
    • FB1, which is an F-test for stable seasonality, performed on the original series.
    • FB8, which is an F-test for stable seasonality, performed on the final ratio of the seasonal-to-irregular components.
    • MSF, which is an F-test for moving seasonality.

As previously mentioned, the CES program generally seasonally adjusts published series at the 3-digit NAICS level and aggregates to the higher levels. However, there are a few cases in which CES seasonally adjusts published series at a level lower than the 3-digit NAICS level. In these instances, CES seasonally adjusts the 3-digit NAICS level indirectly, meaning all of the component or lower level series are seasonally adjusted directly and then aggregated up to the 3-digit level. When this happens, the SERIES spec is replaced by the COMPOSITE spec in the specification file of the 3-digit series.

9. COMPOSITE spec

COMPOSITE{

TITLE = "Construction of buildings"

SAVE = (ISF ISA CMS)

PRINT = BRIEF

NAME = '20236000 - AE'

SAVELOG = (INDTEST INDQ) }

The COMPOSITE spec is used as part of the procedure for obtaining both indirect and direct adjustments of a composite series data series. This spec is required for obtaining composite adjustments and is used in place of the SERIES spec. The COMPOSITE spec can also specify details about the input data series such as the name of the series and which tables are to be printed or stored. The CES implementation employs five options or arguments with the COMPOSITE spec.

  • TITLE — A descriptive title for the series. In this example, the title is "Construction of buildings".
  • SAVE — Specifies output to be saved. In this example, the aggregated time series data with associated dates will be saved in an output file called AE20236000.CMS, the final seasonal factors for the indirect adjustment with associated dates will be saved in an output file called AE20236000.ISF, and the final indirect seasonally adjusted series with associated dates will be saved in an output file called AE20236000.ISA.
  • PRINT — Specifies output to be printed. In this example, BRIEF specifies that only certain tables are printed.
  • NAME — The name of the time series. In this example, the name is "20236000 – AE".
  • SAVELOG — Specifies the diagnostic statistics to be printed to the log file. In this example, the following diagnostics will be printed:
    • IND TEST, which is a test for adequacy of composite adjustment.
    • IND Q, which is an overall index of the acceptability of the indirect seasonal adjustment.

Table of Figures

Use the links below to skip to specific tables and figures describing the CES Seasonal Adjustment Technical Note.

Last Modified Date: March 8, 2024