Revision policies
Saved seasonal adjustment results from multi-processing can be refreshed when new or modified observations are available. JDemetra+ offers several options for refreshing the output, which are in line with the ESS Guidelines on Seasonal Adjustment (2015) requirements.
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To refresh the results, open a workspace via the menu File → Open Workspace. Choose the multi-document option from the Workspace window. Double-click on the SAProcessing of your choice to open the corresponding window and have its name appear in the menu bar.
Opening a multi-document
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After clicking on the SAProcessing item in the menu bar, slide the pointer to the Refresh option. All the refreshing options unfold.
The Refresh menu
The meaning of the refreshing options is summed up in the following table.
| Option | Description |
|---|---|
| Current adjustment (AO approach) | The ARIMA model, outliers and other regression variables are not re-identified, and the values of all associated coefficients are fixed. All new observations are classified as additive outliers and corresponding coefficients are estimated during the regression phase. The transformation type remains unchanged. |
| Partial concurrent adjustment* → Fixed model | The ARIMA model, outliers and other regression variables are not re-identified and the values of all coefficients are fixed. The transformation type remains unchanged. |
| Partial concurrent adjustment* → Estimate regression coefficients | The ARIMA model, outliers and other regression variables are not re-identified. The coefficients of the ARIMA model are fixed but the regression variables coefficients are re-estimated. The transformation type remains unchanged. |
| Partial concurrent adjustment* → Estimate regression coefficients + Arima parameters | The ARIMA model, outliers and other regression variables are not re-identified. All coefficients of the RegARIMA model are re-estimated, for regression variables and ARIMA parameters. The transformation type remains unchanged. |
| Partial concurrent adjustment* → Estimate regression coefficients + Last outliers | Outliers in the last year of the sample are re-identified. All coefficients of the RegARIMA model, regression variables and Arima parameters, are re-estimated. The transformation type remains unchanged |
| Partial concurrent adjustment* → Estimate regression coefficients + Arima model | Re-identification of the ARIMA model, outliers and regression variables, except the calendar variables. The transformation type remains unchanged. |
| Concurrent | Complete re-identification of the whole RegARIMA model, all regression variables and ARIMA model orders. |
* According to the ESS Guidelines on Seasonal Adjustment (2015), partial concurrent adjustment is a family of strategies, in which the model, filters, outliers and calendar regressors are re-identified once a year and a number of the corresponding coefficients and factors are re-estimated every time a new or revised data become available. JDemetra+ offers several types of partial concurrent adjustment: