Approximating missing data points : U.S. Bureau of Labor Statistics

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Bureau of Labor Statistics > Consumer Price Index > Publications > Factsheets

Approximating missing data points

Consumer Price Index (CPI) series for many metropolitan areas are published on a bimonthly schedule, in either even or odd months of the year. The publication schedule of indexes for such areas is given in the 2018 geographic revision area concordance. Information about which CPI series are published in which areas is available in the CPI Handbook of Methods Appendix 7: CPI Items by Publication Level.

Occasionally, a contract might call for an index value for a specific month in a specific area for which data is not available. If both parties agree, the missing data point can be approximated by taking the geometric mean of the index values. This is done by taking the product of the index value for the months immediately before and immediately after the missing month, and then taking the square root of that product. An example is provided in table 1 using the CPI-U all items series for the Washington-Arlington-Alexandria, DC-VA-MD-WV CBSA (CUURS35ASA0).

Table 1, Approximating unpublished index values (CUURS35ASA0)
Quantity	Representation	Value
Index value, September 2022		299.268
Index value, November 2022		300.085
Product of index values	299.268 * 300.085 =	89805.837
Square root of the product of index values	√ 89,805.84 =	299.676
Geometric mean of index values		299.676

Note: Data calculated in this way cannot be interpreted as official CPI series, as the calculation is based on two data points and not on CPI’s aggregation method. Furthermore, if bimonthly CPI data are volatile, then less confidence should be placed in estimates for the missing months. Percent changes based on approximated data should also be considered as unofficial estimates. Examples of volatile series would be apparel, household furnishings and operations, and fuels and utilities.

Last modified date: February 9, 2023