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Consumer Price Index

Measuring price change in the CPI: wireless telephone services

The CPI category telephone services is part of the education and communication major group and has two components: wireless telephone services and residential telephone services. The CPI publishes monthly indexes for telephone services and both of its components at the U.S. level only.

Definition of wireless telephone services

The CPI for wireless telephone services measures changes to the prices of personal wireless (cellular) telephone services. The services priced are primarily specific plans offered by cellular companies and prepaid plans, which include voice calling (talk) and text messaging. Most plans also include cellular data. All service charges, applicable per-plan charges or per-minute call charges, and other charges normally included in a cellular plan, are eligible for pricing.

Pagers, pay phone charges, residential telephone service, and plans that only provide data access without voice calling are excluded. Other phone services, such as long-distance and phone service activation, are excluded unless they are automatically included with a plan at no extra charge. Monthly fees charged by the carrier for the cost of a device are not eligible. Plans designed and marketed for business use are not eligible.

Relative importance

Table A. Relative importance, December 2024
Item Relative importance

Education and communication

5.732

Communication

3.149

Telephone services

1.450

Wireless telephone services

1.281

Residential telephone services

0.169

Information technology, hardware and services

1.644

Internet services and electronic information providers

0.926

Data source

Starting with the release of July 2025 indexes in August 2025, the BLS uses secondary source data and non-traditional index methods to measure price change for the wireless telephone services category of the CPI. One secondary source of data provides a nearly exhaustive sample of wireless telephone service plans available to consumers and their prices and characteristics, and another source provides expenditure data used to weight the service plans. Additional information is available in the white paper “Use of alternative data and methods in the CPI for wireless telephone services”.

Service plan data

BLS purchases wireless-telephone-service-plan price and characteristics data from a market research firm that specializes in the telecommunications industry. The vendor uses both web-scraping and nonautomated methods of data collection to monitor and record the prices and characteristics of service plans offered by wireless telecommunications providers to new customers and existing customers who are upgrading their plans. These data include service plans offered by both mobile network operators (MNOs) and mobile virtual network operators (MVNOs). Service plans and their prices are available nationwide with national pricing. Service plan characteristics include the amount of data included with the plan and hotspot data allowances. The service plan data are received by BLS in the middle of the month in which they will be used in index calculations.

Weighting data

BLS uses household survey data purchased from a market research firm to derive weights for wireless telephone service plans. The vendor conducts annual studies of wireless services by surveying households regarding their wireless telephone ownership experiences. Data purchases and weighting-data updates occur every two years. The weight data are used to properly weight service plans in regression models and in the aggregation of price relatives.

BLS processes the data to prepare it for use, removing entries with incomplete or missing data, ineligible plans, and outliers.  

Index calculation

All service plans in the monthly data are used to build a predictive regression on price, which serves as the foundation of index calculation. Thus, quality improvements introduced by new service plans are immediately and fully integrated into estimates of constant-quality price change.

The general form of the log-level hedonic regression model can be specified as shown in equation 1.

Equation 1: Log-level hedonic regression model

Equation 1: Log-level hedonic regression model

where Zis a vector of observable characteristics for product k. The function h() is estimated with a weighted least squares regression. This hedonic equation varies over time and is estimated each month, allowing the function to detect changes in consumer valuations of the characteristics of wireless telephone services. BLS analysts use statistical tests, machine learning variable selection techniques, and knowledge of the economics of the market to evaluate the hedonic regression models used in this process.

Blending the plan price data with the estimated-expenditure-share weights data allows for the use of weighted regression functions. The effect of using expenditure share-weighted hedonic regressions is that the service plans with the highest expenditure share (the most popular items) are emphasized. The weighted regression model more accurately maps the relationship between prices and characteristics for the mix of service plans purchased by consumers. With this function, hedonic imputation methods (namely, using observable characteristics to impute the missing prices for entering and exiting goods) can be used to correct for quality change introduced by product turnover. See Appendix C of the Monthly Labor Review article “Alternative data sources for high-tech products in the CPI” for more information about the hedonic regression model used in the research that motivated this change to the CPI for wireless telephone services. 

Using the weighted least squares regression, prices are predicted for all service plans in both the current month (t) and previous month (t−1). Additionally, the methodology is extended to predict prices for plans that were not observed—the current month’s prices for exiting plans and the previous month’s prices for entering plans. After predicting prices for time t and t−1, price relatives are calculated and aggregated into an index using a Törnqvist index formula. Plan-level weight shares are assigned to the service plans for both the current month (t) and previous month (t−1). In months when a service plan was not observed, a weight of zero is assigned. The plan’s average weight share is used to weight the plan’s price relative in the aggregation. Since there is no regional variation in the prices of wireless telephone service plans, a single national index is calculated using equation 2.

Equation 2: Törnqvist index formula

Equation 2: Törnqvist index formula

The resulting hedonic index is derived completely from prices predicted by hedonic regression models.  

Taxes, surcharges, and fees

To account for taxes, surcharges, and fees, the national index is replicated to the 32 basic CPI areas and a tax rate specific to wireless telephone services is applied to the untaxed index relatives, or the ratio of the current month’s index to the previous month’s index. For this process, BLS uses tax information gathered by a publicly available, third-party source. This source publishes an annual summary of taxes and fees for wireless services, including average wireless-specific tax rates for both federal and state/local taxes and fees. To calculate an average rate for CPI areas that cross state lines, state rates are population weighted. A similar process of population weighting is used to derive average rates for the nine CPI areas that are aggregates of smaller metropolitan areas. Tax data are updated annually in January.

Finally, to create the U.S.-level index, BLS aggregates the taxed-area relatives using area weights provided by the Consumer Expenditure (CE) survey.

Data

Data for wireless telephone services can be accessed in our online database.

Additional information

Additional information may be obtained from the Consumer Price Index Information Office by email or calling 202-691-7000. Information on the CPI's overall methodology can be found in the BLS Handbook of Methods.

Last Modified Date: August 11, 2025