The Consumer Price Index (CPI) of the Bureau of Labor Statistics (BLS) is a measure of the change in prices of goods and services purchased by urban consumers. The CPI publishes unadjusted price indexes at the national, metropolitan area, and regional levels and seasonally adjusted indexes for selected groups and subgroups of the CPI at the national level where there is a significant pattern of seasonal price change.
Seasonal adjustment removes the effects of recurring seasonal influences from many economic series, including consumer prices. The adjustment process quantifies seasonal patterns and then factors them out of the series to permit analysis of non-seasonal price movements. Changing climatic conditions, production cycles, model changeovers, holidays, and sales can cause seasonal variation in prices. For example, oranges can be purchased year-round, but prices are significantly higher in the summer months when the major sources of supply are between harvests.
Data users who are interested in analyzing general price trends in the economy should use seasonally adjusted indexes. Seasonally adjusted data are usually preferred in the formulation of economic policy and for economic research, because they eliminate the effects of changes that normally occur at the same time and in about the same magnitude every year.
Those who use the CPI in escalation agreements to adjust payments for changes in prices should typically not use seasonally adjusted indexes. Unadjusted indexes are used extensively for escalation purposes because they measure the change in actual prices consumers pay for goods and services. Many collective bargaining contract agreements and pension plans, for example, tie compensation changes to the Consumer Price Index unadjusted for seasonal variation.
No, seasonally adjusted indexes are not calculated for metropolitan areas or regions. Seasonally adjusted indexes are published only for those national price indexes where significant seasonal patterns occur.
The seasonal movement of the all-items index and other aggregations are derived by aggregating seasonally adjusted component indexes. Each January the seasonal status of every index series is reevaluated based upon certain statistical criteria. An index could change its seasonal adjustment status from seasonally adjusted to not seasonally adjusted, or vice versa. During mid-February of each year, when January data are released, new seasonally adjusted indexes are published, and new seasonal adjustment factors for these items are available to data users.
The CPI uses X-13ARIMA-SEATS (auto-regressive integrated moving average) seasonal adjustment software developed by the U.S. Bureau of the Census in 2013. X-13ARIMA-SEATS was developed as an improvement over the previously used X-11-ARIMA and X-12-ARIMA software. X-13ARIMA-SEATS uses the X-11 seasonal adjustment method in conjunction with regression-ARIMA modeling for intervention analysis and data extension.
The technique of intervention analysis also is used in the seasonal adjustment of consumer price indexes to provide more accurate CPI data. This process offsets the effects that extreme price volatility would otherwise have on the estimates of seasonally adjusted data.
Intervention analysis is the prior adjustment of an index series before the calculation of the seasonal factors. Prior adjustment may be called for if a level shift or an outlier occurs. (A level shift occurs when a good or service undergoes a unique, large, and rapid change in price level. An outlier is an extreme value for a particular month.) An example would be a large decrease in the price of gasoline due to the breakdown of an oil cartel. Removal of the level shift gives a clearer seasonal pattern and results in seasonal factors that are a better “fit” for the series. The seasonal factors are then applied to the unadjusted data (without any prior adjustment) to calculate the seasonally adjusted index. When a level shift or outlier exists, intervention analysis helps to calculate more accurate seasonally adjusted data.
The seasonal factors for all items at the U.S City Average level are created from an aggregation of 81 components. The list of components to aggregation of the all items index is available on the CPI seasonal adjustment homepage. Seasonal factors for dependently derived series, such as all items, are available along with the index values that are published for a particular month. Since the relative importance of components change each month as indexes advance, the seasonal factors for aggregate series are not knowable in advance.
The seasonal factor can be divided into a non-seasonally adjusted index to derive the seasonally adjusted index. The seasonal factors table on our CPI seasonal adjustment homepage provide which series are dependently vs independently derived throughout the year.
The CPI program has more details on the X-13ARIMA-SEATS seasonal adjustment method, the intervention analysis technique, events treated as interventions, and seasonal adjustment factors. For additional information on seasonal adjustment in the CPI, please contact us at (202) 691-6968 or email@example.com.
For additional BLS-wide information about seasonal adjustment links, seasonal data, and research papers, please click the "Search" link at the top of this page. Then type the keywords "seasonal adjustment" in the keyword input field and select the "Search Now" button.
Last Modified Date: February 10, 2022