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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Modernizing the Consumer Price Index for the 21st Century. Washington, DC: The National Academies Press. doi: 10.17226/26485.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Modernizing the Consumer Price Index for the 21st Century. Washington, DC: The National Academies Press. doi: 10.17226/26485.
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Prepublication Copy Uncorrected Proofs Modernizing the Consumer Price Index for the 21st Century Panel on Improving Cost-of-Living Indexes and Consumer Inflation Statistics in the Digital Age Committee on National Statistics Division of Behavioral and Social Sciences and Education A Consensus Study Report of

Prepublication Copy—Uncorrected Proofs THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW Washington, DC 20001 This activity was supported by a contract between the National Academies of Sciences, Engineering, and Medicine and the U.S. Department of Labor under contract 1625DC-19-C-0008. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project. International Standard Book Number-13: 978-0-309-XXXXX-X International Standard Book Number-10: 0-309-XXXXX-X Digital Object Identifier: https://doi.org/10.17226/26485 Additional copies of this publication are available from the National Academies Press, 500 Fifth Street, NW, Keck 360, Washington, DC 20001; (800) 624-6242 or (202) 334-3313; http://www.nap.edu. Copyright 2022 by the National Academy of Sciences. All rights reserved. Printed in the United States of America Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2022. Modernizing the Consumer Price Index for the 21st Century. Washington, DC: The National Academies Press. https://doi.org/10.17226/26485.

Prepublication Copy—Uncorrected Proofs The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president. The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. John L. Anderson is president. The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president. The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine. Learn more about the National Academies of Sciences, Engineering, and Medicine at www.nationalacademies.org.

Prepublication Copy—Uncorrected Proofs Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee’s deliberations. Each report has been subjected to a rigorous and independent peer-review process and it represents the position of the National Academies on the statement of task. Proceedings published by the National Academies of Sciences, Engineering, and Medicine chronicle the presentations and discussions at a workshop, symposium, or other event convened by the National Academies. The statements and opinions contained in proceedings are those of the participants and are not endorsed by other participants, the planning committee, or the National Academies. For information about other products and activities of the National Academies, please visit www.nationalacademies.org/about/whatwedo.

Prepublication Copy—Uncorrected Proofs PANEL ON IMPROVING COST-OF-LIVING INDEXES AND CONSUMER INFLATION STATISTICS IN THE DIGITAL AGE DANIEL E. SICHEL (Chair), Department of Economics, Wellesley College ANA M. AIZCORBE, U.S. Bureau of Economic Analysis JAN DE HAAN, Statistics Netherlands (retired) W. ERWIN DIEWERT, Vancouver School of Economics, University of British Columbia LISA M. LYNCH, Heller School for Social Policy and Management, Brandeis University RAVEN S. MOLLOY, Federal Reserve Board of Governors BRENT R. MOULTON, International Monetary Fund MARSHALL B. REINSDORF, International Monetary Fund LAURA ROSNER-WARBURTON, MacroPolicy Perspectives, LLC LOUISE M. SHEINER, Hutchins Center on Fiscal and Monetary Policy, The Brookings Institution CHRISTOPHER MACKIE, Senior Program Officer MICHAEL SIRI, Associate Program Officer ANTHONY MANN, Program Coordinator FM - v

Prepublication Copy—Uncorrected Proofs COMMITTEE ON NATIONAL STATISTICS ROBERT M. GROVES (Chair), Office of the Provost, Georgetown University LAWRENCE D. BOBO, Department of Sociology, Harvard University ANNE C. CASE, School of Public and International Affairs, Princeton University, Emeritus MICK P. COUPER, Institute for Social Research, University of Michigan JANET M. CURRIE, School of Public and International Affairs, Princeton University DIANA FARRELL, JPMorgan Chase Institute, Washington, DC ROBERT GOERGE, Chapin Hall at the University of Chicago ERICA L. GROSHEN, School of Industrial and Labor Relations, Cornell University HILARY HOYNES, Goldman School of Public Policy, University of California-Berkeley DANIEL KIFER, Department of Computer Science and Engineering, The Pennsylvania State University SHARON LOHR, School of Mathematical and Statistical Sciences, Arizona State University, Emeritus JEROME P. REITER, Department of Statistical Science, Duke University JUDITH A. SELTZER, Department of Sociology, University of California-Los Angeles, Emeritus C. MATTHEW SNIPP, School of the Humanities and Sciences, Stanford University ELIZABETH A. STUART, Department of Mental Health, Johns Hopkins Bloomberg School of Public Health JEANNETTE WING, Data Science Institute and Computer Science Department, Columbia University BRIAN HARRIS-KOJETIN, Director MELISSA CHIU, Deputy Director FM - vi

Prepublication Copy—Uncorrected Proofs Acknowledgments This report reflects the contributions of many colleagues who generously gave of their time and expertise to the project. The United States Bureau of Labor Statistics (BLS) sponsored the study with an eye on continuing their decades-long commitment to the production of high- quality price statistics. As a key official statistic, the Consumer Price Index (CPI) provides critical information to a wide range of stakeholders, including other government agencies, private- and public-sector policy makers, financial market participants, researchers, the media, and the general public. On behalf of my fellow panel members, we thank BLS staff who helped shape the project scope and then provided comprehensive information about the CPI program throughout the study. At the panel’s first meeting, BLS Commissioner William Beach articulated the agency’s strategy for continuing to modernize the CPI and highlighted priorities where the agency is looking for guidance from the panel. The panel also benefitted from expert coordination and sponsor leadership throughout the project from BLS Economist Anya Stockburger (branch chief, Office of Prices and Living Conditions). The panel benefited from presentations on topics central to the panel’s charge by several BLS staff responsible for delivering CPI statistics to the nation on a regular and timely basis. Rob Cage (assistant commissioner for consumer prices and price indexes) and Anya Stockburger discussed opportunities and challenges in the context of BLS’s alternative data initiative. Rob also outlined current and planned work by the agency on price measurement for subpopulation groups, including past efforts to develop indexes defined by income quintiles. Brett Matsumoto (research economist) provided an overview of CPI program approaches to expenditure categories that raise unique measurement challenges such as health care, housing, and high-tech goods. Brendan Williams (economist) provided an overview of the CPI program’s approach to quality assessment for alternative data that helps determine which sources to pursue and approve for use in production. The panel is also grateful to many colleagues conducting research beyond the BLS who presented their work involving innovative use (or planned use) of alternative data for price measurement. This testimony included expert guidance from academic researchers and from practitioners delivering price statistics for agency programs in other countries. Tanya Flower and Helen Sands, Office for National Statistics, discussed ongoing and planned CPI data FM - vii

Prepublication Copy—Uncorrected Proofs transformation for the United Kingdom, including integration of scanner and scraped price data, and the role of these data sources for measuring inflation during the pandemic. Ken Van Loon, Statistics Belgium, described his agency’s use of scanner data and web scraping, and implementation of a multilateral methods in CPI production. Leigh Merrington and Catherine Smyth, Australian Bureau of Statistics, provided a history of their country’s use of scanner data in the CPI and how the agency had gone about implementing data modernization for the program. Heidi Ertl, Statistics Canada, detailed that agency’s CPI modernization plan, highlighting experiences and lessons learned in the process. Claude Lamboray, Eurostat, provided an overview of data quality and statistical issues when alternative data are used as a substitute for, or are blended with, traditional data. Kevin Fox, University of New South Wales, synthesized material presented by all the statistical agencies and offered observations on which approaches are most promising, while highlighting some practical considerations. Several presenters provided essential input on broad methodological price measurement topics, to whom the panel is grateful. Jens Mehrhoff, Deutsche Bundesbank, provided a statistical assessment of probabilistic (survey-based) datasets versus scanner and web-scraped data sources. Alberto Cavallo, Harvard University, and Pilar Iglesias, PriceStats, provided the panel with detailed information on techniques for measuring inflation using online price data, including how data collection and processing of online data could work in the production environment of a statistical agency. Matthew Shapiro, University of Michigan, John Haltiwanger, University of Maryland, and David Johnson, University of Michigan, provided an overview of current efforts to reengineer key economic indicators for the United States using alternative data. They presented findings from their recent research comparing alternative approaches to quality adjustment of price indexes using item-level price and quantity data and company-specific data. Costa Lasiy, Adobe Digital Insights, discussed his company’s Digital Economy Index, which includes a high-frequency index for tracking e-commerce prices. David Byrne, Federal Reserve Board, discussed his research measuring price change for consumer digital access services. One public session was devoted to invitees sharing their research to construct subgroup price indexes paying particular attention to the data demands and methodological issues confronted during such work. Xavier Jaravel, London School of Economics, discussed his work using scanner data to measure differences in prices paid by population subgroups across the income distribution. Greg Kaplan, University of Chicago, described recent research measuring inflation at the household level that revealed price dispersion across subgroups. Dennis Fixler, Bureau of Economic Analysis (BEA), reported on work by his agency to produce distributional statistics of personal income for U.S. households. Chris Payne, UK Office for National Statistics (ONS), described the household cost indexes published by his agency for population subgroups in the UK. Another public session was held on the pricing of housing and shelter, a key CPI component given that it accounts for over 20 percent of consumer units’ expenditures. Jeremy Moulton, University of North Carolina, discussed his research using Zillow data to measure the price of housing services, and offered suggestions for how the data might be useful to BLS in its current approach. Bettina Aten, BEA, described her work on the rental equivalence method of measuring housing services in the regional indexes and national accounts context. Annie De FM - viii

Prepublication Copy—Uncorrected Proofs Champlain, Elspeth Hazell, and Faouzi Tarkhani, all of Statistics Canada, provided a comprehensive overview of methods used by their agency to measure housing price changes, including use of alternative data sources. Robert Hill, University of Graz, followed with a discussion of the potential advantages of a simplified user-cost method as an alternative to rental equivalence for measuring price changes in owner-occupied housing. Brian Adams, BLS, discussed statistical issues pertaining to representativeness of housing data sources that rely disproportionately on prices of apartment rents. Paul Liegey, BLS, and Randy Verbrugge, Cleveland Federal Reserve Bank, also provided valuable perspectives regarding useful directions for use of alternative data sources in the housing component of the CPI program. The panel held a similar session to learn about strategies for improving the accuracy, timeliness, and detail of price measurement for medical care services, specifically health insurance, purchased by consumers. After Brett Matsumoto, BLS, reported on the current use of alternative data sources in the medical care portion of the CPI and Abe Dunn, BEA, described medical care price measurement issues of interest to BEA, the panel heard from a roundtable of experts on the topic. Those providing details on decades of relevant leading-edge research included David Cutler, Harvard University, Matt Fiedler, Brookings Institution, and Martin Gaynor, Carnegie Mellon University. This discussion provided essential input for the panel’s chapter on pricing medical care services. Even with the many contributions detailed above, the panel could not have conducted its work efficiently without the capable staff of the National Academies of Sciences, Engineering, and Medicine. Brian Harris-Kojetin, director of the Committee on National Statistics, provided institutional leadership and overarching guidance about the study process; Kirsten Sampson-Snyder, Division of Behavioral and Social Sciences and Education, coordinated the review process flawlessly; and Paula Whitacre provided thorough final editing that improved the readability of the report. We also thank senior program associate Anthony Mann for his well-organized and efficient logistical support of the panel’s meetings and Michael Siri, associate program officer, for substantive contributions organizing the panel’s meetings and in formatting this report. The panel is especially indebted to Christopher Mackie of the Committee on National Statistics, who was the study director for the project. Chris did an extraordinary job staffing the panel, providing timely coordination and logistical support, critical insights and background on substantive issues, and substantial work in drafting the report as well as drafting the responses to external reviews. Beyond that, the panel chair is especially grateful for Chris’s wise counsel throughout the entire panel process. Finally, and most importantly, I would like acknowledge the collective effort of my fellow panel members who provided deep insights and gave generously of their time throughout the study. This report reflects the collective expertise and commitment of all panel members: Ana M. Aizcorbe, U.S. Bureau of Economic Analysis; Jan de Haan, Statistics Netherlands (retired); W. Erwin Diewert, Vancouver School of Economics, University of British Columbia; Lisa M. Lynch, Heller School for Social Policy and Management, Brandeis University; Raven S. Molloy, Federal Reserve Board of Governors; Brent R. Moulton, International Monetary Fund; Marshall B. Reinsdorf, International Monetary Fund (retired); Laura Rosner-Warburton, MacroPolicy Perspectives, LLC; and Louise M. Sheiner, Hutchins Center on Fiscal and Monetary Policy, The Brookings Institution. This group—chosen for their diverse perspectives, FM - ix

Prepublication Copy—Uncorrected Proofs backgrounds, and deep subject matter knowledge—was a pleasure to work with. Each and every member made substantial substantive contributions to the report as well as maintained their good nature and positive attitude, even as all of our meetings had to be carried out remotely. This Consensus Study Report was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, Engineering, and Medicine in making each published report as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. The panel thanks the following individuals for their review of this report: Alberto F. Cavallo, Business, Government, and the International Economy, Harvard Business School; Julia Coronado, President, MacroPolicy Perspectives, LLC, New York, NY; Edward Coulson, Merage School of Business, University of California, Irvine; Matthew Fiedler, Economic Studies Program, Brookings Institution; Dennis J. Fixler, Chief Economist, Bureau of Economic Analysis; Kevin J. Fox, School of Economics, University of New South Wales, Sydney; Austan D. Goolsbee, Department of Economics, The University of Chicago Booth School of Business; Ariel Pakes, Department of Economics, Harvard University; John J. Stevens, Division of Research and Statistics, Board of Governors of the Federal Reserve System; and Marcel P. Timmer, Growth and Development Economics, University of Groningen. Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations, nor did they see the final draft of the report before its release. The review of the report was overseen by Charles F. Manski, University of Chicago. He was responsible for making certain that an independent examination of this report was carried out in accordance with the standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content rests entirely with the authoring panel and the National Academies. Daniel E. Sichel, Chair Committee on Improving Cost-of-Living Indexes and Consumer Inflation Statistics in the Digital Age FM - x

Prepublication Copy—Uncorrected Proofs Contents Summary 1 Introduction 1.1. The Goals of Price Measurement; Research and Policy Needs 1.2. Motivation for the Study: Building a CPI for the 21st Century 1.3. Charge to the Panel 1.4. Looking Ahead 2 The Potential of Alternative Data Sources to Modernize Elementary Indexes 2.1. Current CPI Methods and Data 2.2. How Alternative Data Sources Can Improve Index Accuracy, Coverage, and Timeliness 2.3. Future Directions Appendix 2A: Multilateral Methods for Price Measurement Appendix 2B: Research on Efforts to Perform Quality Adjustment at Scale 3 Higher Level Aggregation and Shifting Consumer Behavior 3.1. Motivation for Data Modernization 3.2. Approaches to Estimating CPI Weights and Market Basket Composition 3.3. Opportunities, Challenges, and Recommendations 4 Modernizing Difficult-to-Measure Expenditure Categories: Housing/Shelter 4.1. Motivation 4.2. Rental Equivalence Approach to Estimating Price Change for Owner-Occupied Housing 4.3. Alternative Methods to Estimating Price Changes of Owner-Occupied Housing 4.4. Opportunities Created by Alternative Data Sources 4.5. Opportunities Created by Alternative Methods for Estimating Price Change in Owner-Occupied Housing Appendix 4A: Historical Development of Owner Equivalent Rent Estimation at BLS FM - xi

Prepublication Copy—Uncorrected Proofs 5 Modernizing Difficult-to-Measure Expenditure Categories: Medical Care 5.1. Motivation 5.2. Pricing Health Insurance 5.3. Opportunities and Challenges Appendix 5A: Comparison of Indirect and Direct Methods of Pricing Health Insurance Appendix 5B: An Alternative Formulation of the Indirect Method 6 Supplemental Subgroup Price Indexes 6.1. Motivation 6.2. Research Findings 6.3. Opportunities and Next Steps 7 Organizational Considerations and Overarching Guidance 7.1. Coordination within BLS 7.2. Interagency Collaboration 7.3. Collaboration and Communication 7.4. Data Acquisition and Access References Appendix Biographical Sketches of Panel Members FM - xii

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The Consumer Price Index (CPI), produced by the Bureau of Labor Statistics (BLS), is the most widely used measure of inflation in the U.S. It is used to determine cost-of-living allowances and, among many other important private- and public-sector applications, influences monetary policy. The CPI has traditionally relied on field-generated data, such as prices observed in person at grocery stores or retailers. However, as these data have become more challenging and expensive to collect in a way that reflects an increasingly dynamic marketplace, statistical agencies and researchers have begun turning to opportunities created by the vast digital sources of consumer price data that have emerged. The enormous economic disruption of the COVID-19 pandemic, including major shifts in consumers' shopping patterns, presents a perfect case study for the need to rapidly employ new data sources for the CPI.

Modernizing the Consumer Price Index presents guidance to BLS as the agency embarks on a strategy of accelerating and enhancing the use of scanner, web-scraped, and digital data directly from retailers in compiling the CPI. The report also recommends strategies for BLS to more accurately estimate the composition of households' expenditures - or market basket shares - by updating this information more frequently and using innovative survey techniques and alternative data sources where possible. The report provides targeted guidance for integrating new data sources to improve the CPI's estimation of changes in the prices of housing and medical care, two consumer expenditure categories that are traditionally difficult to measure. Because of the urgency of issues related to income and wealth inequality, the report also recommends that BLS identify data sources that would allow it to estimate price indexes defined by income quintile or decile.

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