Modernizing the Consumer Price Index for the 21st Century (2022) / Chapter Skim
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Field-generated data on which the CPI has traditionally relied have become more challenging and expensive to collect, and likely less representative of the overall population. At the same time, the digital revolution has given rise to vast new data sources that can be leveraged for the purpose of tracking consumer prices.
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This summary highlights a subset of the panel's recommendations for modernizing BLS's CPI program. THE POTENTIAL OF ALTERNATIVE DATA FOR CONSTRUCTION OF ELEMENTARY INDEXES Point-of-sale data, household-generated home scanner data, and data scraped from the web are the primary "nontraditional" data sources that have been successfully exploited for price measurement.
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One important benefit of household-based scanner data is that purchases made at retailers that do not participate in point-of-sale programs can, in principle, be captured. Data collection centered around those making purchases also enables information on consumer characteris tics to be collected in a way that can be used to construct price indexes for different population subgroups.
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These agencies have navigated key challenges such as managing risks associated with the use of privately collected data and assessing the capac ity of alternative data sources to track product quality changes. Where rapid quality changes are common, such as for high-tech items, combining datasets that include information about product characteristics expands the opportunities for improving price measurement.
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HIGHER-LEVEL AGGREGATION AND SHIFTING CONSUMER BEHAVIOR With the availability of near real-time information from private-sector data sources, coupled with an ever-increasingly dynamic economy, the col lection and dissemination of timely data has become a basic expectation of statistical agencies. While the composition of what consumers buy is always evolving, the shifts were especially dramatic during the pandemic.
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With supplementing and complementing the CE data in mind, BLS should invest in collecting comprehensive data for individual spending using electronic means of payments such as credit/ debit cards or electronic payment processors (e.g., PayPal or Stripe)
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For example, Statistics Canada (2021) published a special edition price index using credit and debit card data supplied by the Bank of Canada and alternative weights based on na tional accounts data "to account for pandemic related expenditure shifts at more detailed levels of geography and CPI components." Longer-Term Planning The strategy outlined above presumes that BLS will adopt a data ap proach for establishing upper-level expenditure weights that blends data from national accounts and private companies.
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By contrast, the CPI Housing Survey only samples each housing unit every six months, which is problematic in times when rents change rapidly. In addition to their value in measuring rent changes, alternative infor mation sources -- including property tax records and American C ommunity Survey data -- could be used in conjunction with the CPI Housing S urvey.
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The direct approach involves estimating total health insurance premium prices; the indirect approach involves pricing health insurance using prices of medi cal care blended with information about retained earnings of insurance providers. The underlying logic of the indirect approach is to separate out the prices of medical care goods and services from the portion of insur ance premiums retained by insurance companies to cover administrative costs and profits.
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Supplemental Subgroup Price Indexes Price indexes and other economic statistics tailored to describe and track the experiences of specific population subgroups are a growing research and policy need. The rationale for producing price indexes for population subgroups is clear for purposes such as adjusting Social S ecurity benefits and marginal tax rates or for specifying transfer payments for which only certain groups are eligible.
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For this reason, the next generation of empiri cal studies on inflation inequality will need to draw on additional, alterna tive data sources -- perhaps most importantly, a household-based scanner recording program that captures prices, quantities, and item characteristics of purchases made by surveyed respondents. The above-described research linking individuals to their purchases strongly suggests the need for approaches that blend multiple data sources -- encompassing survey data that cover the full consumption basket, including item categories for which electronic transaction data are still incomplete, and commercial data sources that allow deep analyses of prices paid and product detail -- in a way that accounts for the full range of consumer expenditures.
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