Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/26116.html
   My bibliography  Save this paper

Re-engineering Key National Economic Indicators

Author

Listed:
  • Gabriel Ehrlich
  • John Haltiwanger
  • Ron Jarmin
  • David Johnson
  • Matthew D. Shapiro
Abstract
Traditional methods of collecting data from businesses and households face increasing challenges. These include declining response rates to surveys, increasing costs to traditional modes of data collection, and the difficulty of keeping pace with rapid changes in the economy. The digitization of virtually all market transactions offers the potential for re-engineering key national economic indicators. The challenge for the statistical system is how to operate in this data-rich environment. This paper focuses on the opportunities for collecting item-level data at the source and constructing key indicators using measurement methods consistent with such a data infrastructure. Ubiquitous digitization of transactions allows price and quantity be collected or aggregated simultaneously at the source. This new architecture for economic statistics creates challenges arising from the rapid change in items sold. The paper explores some recently proposed techniques for estimating price and quantity indices in large-scale item-level data. Although those methods display tremendous promise, substantially more research is necessary before they will be ready to serve as the basis for the official economic statistics. Finally, the paper addresses implications for building national statistics from transactions for data collection and for the capabilities and organization of the statistical agencies in the 21st century.

Suggested Citation

  • Gabriel Ehrlich & John Haltiwanger & Ron Jarmin & David Johnson & Matthew D. Shapiro, 2019. "Re-engineering Key National Economic Indicators," NBER Working Papers 26116, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:26116
    Note: EFG ME PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w26116.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ian Crawford & J. Peter Neary, 2023. "New Characteristics and Hedonic Price Index Numbers," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 665-682, May.
    2. Feenstra, Robert C, 1994. "New Product Varieties and the Measurement of International Prices," American Economic Review, American Economic Association, vol. 84(1), pages 157-177, March.
    3. Diewert, W, Erwin & Feenstra, Robert, 2017. "Estimating the Benefits and Costs of New and Disappearing Products," Microeconomics.ca working papers tina_marandola-2017-12, Vancouver School of Economics, revised 19 Dec 2017.
    4. Ariel Pakes, 2003. "A Reconsideration of Hedonic Price Indexes with an Application to PC's," American Economic Review, American Economic Association, vol. 93(5), pages 1578-1596, December.
    5. C. Lanier Benkard & Patrick Bajari, 2005. "Hedonic Price Indexes With Unobserved Product Characteristics, and Application to Personal Computers," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 61-75, January.
    6. W. Erwin Diewert & Robert C. Feenstra, 2021. "Estimating the Benefits of New Products," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 437-473, National Bureau of Economic Research, Inc.
    7. Colin J. Hottman & Stephen J. Redding & David E. Weinstein, 2016. "Quantifying the Sources of Firm Heterogeneity," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1291-1364.
    8. Ron S. Jarmin, 2019. "Evolving Measurement for an Evolving Economy: Thoughts on 21st Century US Economic Statistics," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 165-184, Winter.
    9. Gabriel Ehrlich & John Haltiwanger & Ron Jarmin & David Johnson & Matthew D. Shapiro, 2019. "Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 438-443, May.
    10. Lucia Foster & John Haltiwanger & Shawn Klimek & CJ Krizan & Scott Ohlmacher, 2015. "The Evolution of National Retail Chains: How We Got Here," Working Papers 15-10, Center for Economic Studies, U.S. Census Bureau.
    11. Matthew D. Shapiro & David W. Wilcox, 1996. "Mismeasurement in the Consumer Price Index: An Evaluation," NBER Chapters, in: NBER Macroeconomics Annual 1996, Volume 11, pages 93-154, National Bureau of Economic Research, Inc.
    12. Tim Erickson & Ariel Pakes, 2011. "An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods," American Economic Review, American Economic Association, vol. 101(5), pages 1707-1738, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Crystal Konny, 2020. "Modernizing data collection for the Consumer Price Index," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 55(1), pages 45-52, January.
    2. Gabriel Ehrlich & John Haltiwanger & Ron Jarmin & David Johnson & Matthew D. Shapiro, 2019. "Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 438-443, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gabriel Ehrlich & John Haltiwanger & Ron Jarmin & David Johnson & Matthew D. Shapiro, 2019. "Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 438-443, May.
    2. Gabriel Ehrlich & John C. Haltiwanger & Ron S. Jarmin & David Johnson & Ed Olivares & Luke W. Pardue & Matthew D. Shapiro & Laura Zhao, 2023. "Quality Adjustment at Scale: Hedonic vs. Exact Demand-Based Price Indices," NBER Working Papers 31309, National Bureau of Economic Research, Inc.
    3. Xosé-Luís Varela-Irimia, 2014. "Age effects, unobserved characteristics and hedonic price indexes: The Spanish car market in the 1990s," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 5(4), pages 419-455, November.
    4. David M. Byrne & Stephen D. Oliner & Daniel E. Sichel, 2018. "How Fast are Semiconductor Prices Falling?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(3), pages 679-702, September.
    5. Crystal Konny, 2020. "Modernizing data collection for the Consumer Price Index," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 55(1), pages 45-52, January.
    6. Philippe Aghion & Antonin Bergeaud & Timo Boppart & Peter J. Klenow & Huiyu Li, 2019. "Missing Growth from Creative Destruction," American Economic Review, American Economic Association, vol. 109(8), pages 2795-2822, August.
    7. Daan Freeman & Robert Inklaar & W. Erwin Diewert, 2021. "Natural Resources and Missing Inputs in International Productivity Comparisons," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(1), pages 1-17, March.
    8. Emi Nakamura & Jón Steinsson, 2012. "Lost in Transit: Product Replacement Bias and Pricing to Market," American Economic Review, American Economic Association, vol. 102(7), pages 3277-3316, December.
    9. Patrick Bajari & Zhihao Cen & Victor Chernozhukov & Manoj Manukonda & Jin Wang & Ramon Huerta & Junbo Li & Ling Leng & George Monokroussos & Suhas Vijaykunar & Shan Wan, 2023. "Hedonic prices and quality adjusted price indices powered by AI," CeMMAP working papers 08/23, Institute for Fiscal Studies.
    10. Thomas von Brasch & Arvid Raknerud, 2022. "The impact of new varieties on aggregate productivity growth," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 646-676, July.
    11. OTA Rui & ZHANG Lili, 2020. "Declining Demand and Product Quality: An Empirical Study of the Japanese PC Monitor Market," Discussion papers 20033, Research Institute of Economy, Trade and Industry (RIETI).
    12. Seidu Dauda & Abe C. Dunn & Anne E. Hall, 2019. "Are Medical Care Prices Still Declining? A Systematic Examination of Quality-Adjusted Price Index Alternatives for Medical Care," BEA Working Papers 0166, Bureau of Economic Analysis.
    13. Ana Aizcorbe & Nicole Nestoriak, 2010. "Price Indexes for Drugs: A Review of the Issues," BEA Working Papers 0050, Bureau of Economic Analysis.
    14. Stephen J. Redding & David E. Weinstein, 2017. "Aggregating from Micro to Macro Patterns of Trade," NBER Working Papers 24051, National Bureau of Economic Research, Inc.
    15. Kancs, d'Artis & Persyn, Damiaan, 2019. "Welfare Gains from the Variety Growth," Working Papers 2019-01, Joint Research Centre, European Commission.
    16. Rojas, Christian & Jaenicke, Edward C. & Page, Elina T., 2024. "Shrinkflation? Quantifying the impact of changes in package size on food inflation," 2024 Annual Meeting, July 28-30, New Orleans, LA 343770, Agricultural and Applied Economics Association.
    17. Brynjolfsson, Erik & Collis, Avinash & Diewert, W. Erwin & Eggers, Felix & Fox, Kevin J., 2019. "GDP-B: Accounting for the Value of New and Free Goods in the Digital Economy," OSF Preprints sptfu, Center for Open Science.
    18. Dakshina G. De Silva & Nidhi Thakur & Mengzhi Xie, 2013. "A hedonic price analysis of hearing aid technology," Applied Economics, Taylor & Francis Journals, vol. 45(16), pages 2315-2323, June.
    19. Irac, D., 2008. "Access to new imported varieties and total factor productivity: Firm level evidence from France," Working papers 204, Banque de France.
    20. Liang Bai & Sebastian Stumpner, 2019. "Estimating US Consumer Gains from Chinese Imports," American Economic Review: Insights, American Economic Association, vol. 1(2), pages 209-224, September.

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:26116. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.