Supports the modeling and seasonal adjustment methodology for U.S. Census Bureau's X12-ARIMA in Excel.

Seasonal adjustment is a statistical method for removing the seasonal component of a time series when analyzing non-seasonal trends. It is normal to report seasonally adjusted data for unemployment rates to reveal the underlying trends in labor markets. Many economic phenomena have seasonal cycles, such as agricultural production and consumer consumption (e.g. greater consumption leading up to Christmas). It is necessary to adjust for this component in order to understand what underlying trends are in the economy; thus, official statistics are often adjusted to remove seasonal components.

Different statistical research groups have developed different methods of seasonal adjustment, including the United States Census Bureau's X12 ARIMA, the Bank of Spain's TRAMO/SEATS, and STAMP, developed by a group led by S. J. Koopman. Each group provides software supporting their particular methods.

NumXL fully supports the modeling methodology for X12 ARIMA in Excel: you can reference the input data in the spreadsheet, specify the different options (e.g. prior adjustment, outlier treatment, etc.) of X12 ARIMA all in Excel through an intuitive wizard, and display the seasonal-adjusted time series or forecast.

X12-ARIMA Examples

Tutorial Videos

X12-ARIMA Function

X12-ARIMA in NumXL Techinal Note

Starting with version 1.57, NumXL will support U.S. Census X12-ARIMA modeling including seasonal adjustment...


In this tutorial, we’ll demonstrate the steps to compute seasonal adjusted time series using the function...