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Handbook of Methods Producer Price Indexes Presentation

Producer Price Indexes: Presentation

The Producer Price Index (PPI) measures average changes in prices received by domestic producers for their output. Most of the information used in calculating producer price indexes is obtained through the systematic sampling of industries. Known until 1978 as the Wholesale Price Index, or WPI, the PPI is one of the oldest continuous systems of statistical data published by the Bureau of Labor Statistics (BLS), as well as one of the oldest economic time series compiled by the federal government. In 1978, the WPI was rebranded as the Producer Price Index, with its main publication system becoming the Stage-of-Processing (SOP) System, headlined by the PPI for Finished Goods. The Final Demand–Intermediate Demand(FD–ID) system replaced the PPI SOP system as PPI’s primary aggregation model with the release of data for January 2014. The FD–ID model expands coverage beyond that of the SOP system through the addition of services, construction, exports, and government purchases.

Publications

The PPI website provides access to news releases, databases, the PPI Detailed Report, articles, and additional information such as preformatted tables, publications, reference files, and explanatory documents.

PPI news releases are usually issued in the second or third week of the month following the reference month. The specific monthly release dates for a given year are posted to the BLS website prior to the beginning of the calendar year. PPI news releases focus on major Final Demand–Intermediate Demand(FD–ID) categories and the commodity indexes that explain changes in the FD–ID indexes. For more information about the FD–ID aggregation system, see the concepts section.

Database access is available at the PPI databases website or by contacting the PPI program staff at ppi-info@bls.gov or (202) 691-7705. The PPI databases website provides tools that permit users to download nearly all current and discontinued PPI time-series data.

The monthly PPI Detailed Report is available on the PPI website on the day PPI data are issued. This report includes all publishable data within the revision period for the PPI family of indexes. In addition, the publication contains a narrative section explaining the most important price movements within the major FD–ID categories for that month. When appropriate, special technical articles discuss the latest changes in the PPI sample, updates in seasonal adjustment factors or weights, or other changes in methodology or presentation. Occasionally, longer articles provide in-depth explanation of the economic background underlying recently observed price movements.

Articles that contain analysis of PPI data are published in the Monthly Labor Review and Beyond the Numbers publications on the BLS website. All other program information, including descriptions of non-standard methodologies for specific industries, special notices announcing program changes, and frequently asked questions are available on the PPI website.

Seasonally adjusted data

Because price data are used for various purposes, BLS publishes seasonally adjusted data, as well as unadjusted data, each month. For economic analysis of short-to medium-term (within-year) price trends, seasonally adjusted data usually are preferred because they are designed to eliminate the effect of changes that normally occur at about the same time and in about the same magnitude each year. These factors include normal weather patterns, regular production and marketing cycles, new-model-year motor vehicle introductions, seasonal discounts, and holidays. Data that are seasonally adjusted more clearly reveal within-year trends, such as over-the-month, quarterly, semi-annual, and annualized rates of change.

Normally, over-the-month and quarterly analyses of PPI price movements are based on seasonally adjusted data. Unadjusted data are used for analysis when a series has not been selected for seasonal adjustment because it does not exhibit seasonality, as well as for the analysis of year-over-year trends. In addition, because seasonal adjustment is a tool for enhancing economic analysis, indexes that BLS deemphasizes for this purpose are deliberately not seasonally adjusted. In particular, those PPIs which are subject to the multiple-counting problem (described in both the history and concepts sections), including the All Commodities Index and high-level 2-digit commodity indexes for the major commodity groupings, are not available on a seasonally adjusted basis.

The unadjusted versions of PPI data are of primary interest to those who need information that can be more readily related to the dollar values of transactions, such as those using the PPI for contract price adjustment purposes.

For a detailed description of PPI methods pertaining to seasonal adjustment, visit the PPI Seasonal Adjustment page.

Index revision

Beginning in the 1970s and continuing through October 2021, PPIs were routinely subject to revision 1 time, 4 months after original publication, to reflect late reports and corrections reported by respondents. Once revised, not-seasonally-adjusted indexes were considered final. Effective with the release of data for November 2021, PPI index revisions include iterative updates for the 3 interim months after first issuance prior to posting of final indexes 4 months after original publication. This change in procedures means that effective with data for November 2021, indexes undergo five iterative updates from first issuance through final posting. This modification in publication standards shifts index revisions and accompanying over-the-month percentage changes to the appropriate month on an immediate basis. Under the prior method, final PPIs could experience larger revisions because they had not been updated since first issuance. In addition, under the previous method, first-issued percentage changes for the most recent month had embedded in them all the revisions from the interim months.

Despite this change in index revision procedures, when PPIs are first released, they typically are based on a substantial portion of the total number of responses that eventually will be received from respondents. Hence, subsequent revisions normally are minor, especially at more highly aggregated grouping levels. Seasonally adjusted index revisions are treated differently by PPI. Seasonally adjusted indexes also are recalculated on an annual basis going back 5 years, as described in the calculation section. Changes in previously published data caused by a processing error are indicated by a notice on the PPI homepage, the PPI Detailed Report, and the errata webpage.

Index precision

Effective with PPI data for July 2021, PPI updated procedures to include index publication to three-decimal-place precision. Prior to this update, PPIs were published to a level of precision of one decimal place. This modification allows users to calculate percent changes between indexes more accurately. Using indexes posted at three-decimal-place precision permits users to accurately calculate a percent change to the one-hundredth of a percent (two-decimal place precision); whereas, under the prior method percentage changes calculated to the tenth of a percent still included substantial rounding issues. For presentation purposes, PPI tabular products publish index levels to three-decimal precision, but percentage changes still are published to one-decimal-place precision. (See example of percentage change calculation that follows.)

Variance estimates

The PPI program began publishing an annual variance estimates report in 2016, with 2015 data. This report is produced annually, after data for the prior calendar year are final. The variance estimates report includes measures of 1-month and 12-month median standard errors. To provide a frame of reference, corresponding 1-month and 12-month measures of median absolute percentage change also are provided. The PPI data in this report include information pertaining to the FD–ID structure, PPI commodity-based indexes, and PPI NAICS-based indexes. Standard error, a commonly used measure of sampling variability, may be used to calculate a confidence interval around a corresponding sample percent change. Standard error measures estimate the sample distribution, or spread, of the sample estimates from the true population value. For a detailed description of PPI methods pertaining to the calculation of variance estimates, as well as, to access the archive of annual PPI variance reports, visit the section on variances of the PPI webpage.

Calculating index changes

Movements of price indexes from one data point to another should be expressed as percent changes, rather than as changes in index points, because the latter are affected by the level of the index in relation to its base period while the former are not. For example, an index change from 100 to 110 reflects a 10-percent increase in prices, while an index change from 200 to 210 (still 10 index points) reflects a 5-percent advance in prices.

Conceptualized as a shift in dollar values, an increase of 10 percent from the base period (November 2009) for the Final Demand index would be shown as an index level of 110.0 and would be expressed in dollars as, “Prices received by domestic producers of a systematic sample of final-demand products have risen from $100 in November 2009 to $110 today.” Likewise, a current index of 90.0 would indicate that prices received by producers of final-demand products have fallen 10 percent from what they were in the base period.

The following example of the computation of index point change and 12-month percent change is based on the unadjusted PPI for final demand for September 2021 and September 2022:

As stated earlier, PPI began publishing index values to three-decimal precision beginning in July 2021. For presentation purposes, percent changes published using these more precise index data continue to be posted in publication tables using one-decimal precision. However, data users can calculate more accurate, two-decimal-place percent changes using the three-decimal precision index values. For example, the 8.5-percent increase in the Final Demand index calculated above could be more precisely calculated to 8.48 percent, based on the index levels for September 2021 and September 2022.

Uses and limitations of the PPI

Producer price indexes are used for many purposes by government, business, labor, universities, other organizations, and the public.

Economic indicator

PPI data are some of the nation’s most closely watched indicators of economic health. Movements in the FD–ID indexes have been used to study the transmission of inflation through the economy, including the stages of production, and as a potential leading indicator of retail inflation as measured by the BLS Consumer Price Index (CPI). Within the FD–ID aggregation system, the final demand structure tracks price changes for goods, services, and construction sold for personal consumption, as capital investment, to government, and for export. The intermediate demand portion of the system tracks price changes for goods, services, and construction sold to businesses as inputs to production. Two treatments of intermediate demand are constructed by PPI, one by commodity type and another by production flow. From an intermediate-demand perspective, the commodity-type treatment tracks price movements for services purchased by businesses, in addition to price movements for processed and unprocessed goods. The production flow treatment of intermediate demand tracks price changes as they advance through the various stages of production. This treatment provides an opportunity to systematically monitor and assess to what degree changes in rates of inflation faced by producers at earlier stages of production are transmitted to subsequent stages, including final demand. The commodity-type treatment of intermediate demand also provides an opportunity to track inflation pass-through; however, this treatment, while less complicated, is also less systematic and rigorous in its construction. Taken in its entirety, the FD–ID system is well suited for analyzing the inflation transmission process.^⁠1 For a detailed explanation of the PPI FD–ID aggregation system, visit the PPI Final Demand-Intermediate Demand webpage.

Underlying rate of inflation

Because prices for food, energy, and trade services have tended to be volatile, over time some economists have come to focus attention on indexes that measure price changes that exclude these areas. These economists believe that the special indexes excluding components commonly exhibiting short-term volatility provide clearer measures of what is sometimes referred to as the underlying rate of inflation. The highest profile index that excludes these components is the PPI for final demand less foods, energy, and trade services; although, other exclusionary indexes also are calculated.

Although some users of price index data attempt to employ PPI data as a potential leading indicator of other measures of inflation, there are many reasons that price movements in the PPI and other indicators can diverge. Information explaining the differences between the PPI and other government indicators, as well as information explaining why the value of using PPI as a leading indicator of CPI is limited, is available in this Monthly Labor Review article.

Some users of price index data are interested in comparing PPI NAICS-based data with import price data available from the International Price Program. However, there are important differences between PPI and import price data that users should be aware of before comparing data series from the two programs.

Deflator

PPI data are used by a variety of organizations to remove the effects of price changes from their economic data. PPI data at all levels of industry and commodity aggregation can be used to deflate dollar values expressed in current dollars to constant-dollar values for a variety of economic time series, such as inventories, sales, shipments, and capital equipment replacement costs. For example, the U.S. Department of Commerce uses PPI data to calculate the gross domestic product (GDP) deflator, and many of its components. To illustrate the deflation concept, suppose that nominal values of shipments for a given industry have doubled over a 10-year span. If the PPI for that industry has tripled over the same time span, then the “real” (that is, inflation-adjusted) value of shipments for the industry has declined. Higher prices would more than account for the doubling of dollar shipment values, and physical volume would implicitly have fallen.

Private business uses

Private firms use PPI data to assist their operations in a variety of ways, in addition to using the data for general economic analysis or as a deflator of some other quantity. PPIs frequently are cited for price escalation purposes in long-term sales or purchase contracts as a means of protecting both the buyer and the seller from unanticipated surges or drops in prices. A PPI data user survey done in 2012 suggests that trillions of dollars in contract values are tied to PPIs through these price escalation clauses, which are common in both government and private sector contracts.^⁠2

Companies also use PPI data to compare changes in material costs they incur against changes in the PPI for the material in question. Similarly, companies can compare changes in the prices they charge for their own output with changes in the PPI for the same kind of product. PPI data also are employed in econometric models, forecasting, market analysis, and academic research. PPIs are frequently used in last-in, first-out (LIFO) inventory accounting systems by firms wishing to avoid the kind of “phantom profits” that might appear on their books with a first-in, first-out (FIFO) inventory accounting system.

Discontinued and unavailable data

Those wishing to follow PPI data for a particular series over a prolonged timespan should be aware that BLS is more likely to discontinue highly detailed indexes than aggregated indexes. For example, during the industry resampling process, an industry-level index commonly will maintain continuity, but indexes for detailed products within that industry may be discontinued and replaced by indexes for items that are new or that previously had not been selected for tracking.

In addition, as a voluntary survey where companies provide proprietary pricing and product information, PPI goes to great lengths to ensure confidentiality for survey respondents. Therefore, finely detailed indexes also may be vulnerable to temporary suspension of publication, due to low response rates.

When a detailed index falls out of publication, either temporarily or permanently, BLS routinely recommends that users who follow that index: (1) choose another detailed index within the same product grouping, (2) switch their attention to a more highly aggregated grouping index, or (3) consider using a similar index under the commodity index structure, if the original index for tracking was industry based. In reference to option 3, commodity-based indexes for similar products might meet publication criteria even when the equivalent industry-based PPI falls out of publication, because commodity-based PPIs are calculated irrespective of industry of origin and potentially might include price data for similar products produced by other industries.