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We produce relative importance of components in the Consumer Price Index for All Urban Consumers (CPI-U) and the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). These data are to be used in conjunction with the CPI-U and CPI-W released in that same year. BLS publishes this data once a year, using December data. Relative importance data is also published monthly at the U.S. level in the news release tables.

Table 1 contains data for the U.S. city average for all categories. In years where the weights used in the construction of the CPI are updated, table 1 is produced using both the old and new weights to allow users to compare them. Tables 2 through 6 contain data for selected categories for the regions, metropolitan areas, population size classes, and cross-classifications of area and population size class. Table 7 contains the relative importance of the **all items** index for the U.S. city average and size class, region and region size class, and metropolitan areas.

The relative importance of a component is its expenditure or value weight expressed as a percentage of all items within an area or an area within the U.S. When the value weights are collected they represent average annual expenditures, and their relative importance ratios show approximately how the index population distributes expenditures among the components. Relative importance ratios represent an estimate of how consumers would distribute their expenditures as prices change over time.

Relative importance ratios cannot be used as estimates of current spending patterns or as indicators of changing consumer expenditures in the intervals between weight revisions because consumption patterns are influenced by factors other than price change. These factors include income, variations in climate, family size, and availability of new and different kinds of goods and services.

Relative importance ratios of components in the national or local area Consumer Price Indexes can be used in the construction of indexes for special combinations of items. In such instances, relative importance ratios are used as weights to combine relative changes in prices of the selected components over specified periods.Additional information on the procedure for deriving index weights from consumer expenditure data is available in the Consumer Expenditure Survey and Consumer Price Index sections of the BLS Handbook of Methods.

To estimate a relative importance for a component for a month other than December, one can use its previous published relative importance and update it by published price changes. For example, suppose you want to estimate the relative importance of **energy** for the CPI-U in September 2017.

You need the published relative importance for** energy** for December 2016 and the December 2016 and Sept.ember 2017 indexes for **energy** and for **all items**. Enter the weights and indexes for these two item categories (see table A). The updated weight column is the December published weight times the relative change between December 2016 and September 2017. In this example, the updated weight for **energy** is 7.039 * (215.711/193.306) = 7.8549. For **all items**, the updated weight is 100.000 * (246.819/241.432) = 102.2313. To calculate the updated relative importance for **energy** where the weight for **all items** is normalized to 100, divide the updated weight for **energy** by the updated weight for **all items**, times 100. In this example, the estimated relative importance for **energy** in September 2017 is (7.8549 / 102.2313) X 100 = 7.683.

Item | Published relative importance Dec. 2016 | Index Dec. 2016 | Index Sep. 2017 | Updated weight Sep. 2017 | Updated weight Sep. 2017 (normalized so that all items=100) |
---|---|---|---|---|---|

Energy |
7.039 | 193.306 | 215.711 | 7.8549 | 7.683 |

All items |
100.000 | 241.432 | 246.819 | 102.2313 | Normalized to 100.000 |

Continuing the above example, **energy **prices increased 6.4 percent over the 12 months ending October 2017, while the **all items** index increased 2.0 percent. How does one figure out the "contribution" of the **energy** component to the **all items** change? Asked another way, what proportion of the **all items** increase can be attributed to the **energy** component?

To calculate a 12=month contribution, use the relative importance for the beginning of the 12-month period in question. In this case, we need the October 2016 relative importance for **energy**, which is 7.084. (Relative importance for any month can be located in the archived CPI news releases in the month following the month in question; the October 2016 relative importance is in the November 2016 news release.)

We can then follow a procedure similar to that in calculating the updated relative importance, multiplying the values by the ratio of index changes.

Item | October 2016 relative importance | October 2016 index level | October 2017 index level | Updated weight October 2017 | Change in weight | Contribution to all items movement |
---|---|---|---|---|---|---|

All items |
100.000 | 241.729 | 246.663 | 102.041 | 2.041 | |

Energy |
7.084 | 194.786 | 207.290 | 7.539 | .455 | .223 |

The ratio of the difference in the change in weight of the component to the change in weight of **all items**, in this case 0.223, tells us the contribution. Converting this to a percent, **energy** accounted for 22.3 percent of the change in the **all items** index.

This same procedure can be used to calculate a contribution for a 1-month change, or over several months. The relative importance at the beginning of the period should always be the starting point.

Note that if the 12-month period crosses a biennial weight update (January of even years), the calculation will have to be done in multiple parts.

- December 2021
- Table 1, U.S. City Average using 2019-2020 weights (HTML)
- Table 1, U.S. City Average using 2017-2018 weights (HTML)
- Tables 1 - 7, Relative Importance of Components in the Consumer Price Index, all areas (XLSX)
- Table 1, Relative Importance of Components in the Research Consumer Price Index for Americans 62 years of age and older (R-CPI-E) (XLSX)

The CPI measures the change in the cost of the set of goods and services purchased by consumers from one time period to the next. In the first 50 years of producing the CPI, the BLS updated the spending weights every 10 years based on information from several years earlier collected in periodic surveys. Over time the Consumer Expenditure Surveys (CE) became continuous and the BLS began updating the CPI spending weights every two years, beginning with January 2002 indexes.

The biennial spending weight update reflects consumer spending from two to three years prior. For example, consumer purchases made in 2017 and 2018 were used by BLS as the spending weights in January 2020 through December 2021 CPI-U, CPI-W and R-CPI-E indexes. The overall goal of the CPI-U index is to use consumer spending from as recent a time period as possible, and hold the set (or more precisely, the quantity mix) of goods and services purchased fixed over a period of time until new spending weights can be introduced. In general, estimates of current period inflation tend to be higher when calculated with outdated spending weights when compared to inflation estimates calculated with more current spending weights. This is because consumers change, or substitute, what they buy over time, often shifting purchases away from items that are becoming relatively more expensive to alternatives whose prices are not rising as fast.

Information on the 2022 weight update is available on the 2022 weight update information page.

**Last Modified Date:** April 21, 2022