Seasonal Adjustment and

Forecasting Solutions for You

Do you need to seasonally adjust your data?

The basic goal of seasonal adjustment is to decompose a time series into several different components including a seasonal component and an irregular component. If we can eliminate the seasonal patterns, the time series are often easier to interpret. Some features of a time series that could be of interest are direction, turning points, and consistency between time series. Identifying seasonal patterns is also useful when forecasting a time series to build seasonal movements into the forecasts.

We can help you set up options for the various types of seasonal adjustment software available, particularly X-12-ARIMA and TRAMO/SEATS.

We offer both project-by-project consulting and a subscription service. For more information, please see our Services page.

Would you like to produce better forecasts?

Forecasting can be difficult, especially if you are dealing with information that contains seasonal patterns, product life-cycles, shifts due to outside forces, or hundreds of other possible events. Though it's impossible to predict the future perfectly, of course, using monthly or quarterly seasonal models for that take cycles, shifts and outliers into account can greatly improve your forecasts.

Would you like to better predict leading economic indicators?

Many government agencies collect and publish time series, and most of the sub-annual indicators are seasonally adjusted. Would you or your company benefit by gaining insight into the seasonally adjusted numbers published every month or quarter? Understanding seasonal adjustment can help us predict what various agencies will say about the economic indicators that they publish.

Do you want to know more about seasonal adjustment?

Catherine teaches a wide range of courses on the subject. More information on courses and other services can be found on the Courses page.

Short of taking a course, how can you learn more about seasonal adjustment? Check out our Frequently Asked Questions (FAQ) and papers pages. We also have some links to free seasonal adjustment software.

We can help!

We are driven by a focus on our customers, working to deliver quality, tested products that are beyond expectations, anticipating needs and responding to requests when needed. Our experience is not only with finding proper methods, but also in putting the methods into production. We believe that solutions to your specific problems mean solutions that can be used in practice and in production, not just a research report.

Catherine has over 22 years experience providing statistical consulting services and over 20 years of experience in time series. Her time series experience includes time series modeling, seasonal adjustment, ARIMA and regARIMA modeling, and setting models and seasonal adjustment options for production. She has extensive experience in seasonal adjustment software (particularly X-12-ARIMA and TRAMO/SEATS), statistical time series models, forecasting, benchmarking, price indices, and quality control.

Roxanne Feldpausch has over 11 years of experience as a statistician and 6 years of experience in time series. Her experience includes modeling time series using regARIMA models and using the models for forecasting, outlier detection, and to aid in seasonal adjustment.

Back to the Top