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How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches

Author

Listed:
  • Erica L. Groshen
  • Brian C. Moyer
  • Ana M. Aizcorbe
  • Ralph Bradley
  • David M. Friedman

Abstract

A key economic indicator is real output. To get this right, we need to measure accurately both the value of nominal GDP (done by Bureau of Economic Analaysis) and key price indexes (done mostly by Bureau of Labor Statisticcs). All of us have worked on these measurements while at the BLS and the BEA. In this article, we explore some of the thorny statistical and conceptual issues related to measuring a dynamic economy. An often-stated concern is that the national economic accounts miss some of the value of some goods and services arising from the growing digital economy. We agree that measurement problems related to quality changes and new goods have likely caused growth of real output and productivity to be understated. Nevertheless, these measurement issues are far from new, and, based on the magnitude and timing of recent changes, we conclude that it is unlikely that they can account for the pattern of slower growth in recent years. First we discuss how the Bureau of Labor Statistics currently adjusts price indexes to reduce the bias from quality changes and the introduction of new goods, along with some alternative methods that have been proposed. We then present estimates of the extent of remaining bias in real GDP growth that stem from potential biases in growth of consumption and investment. And we take a look at potential biases that could result from challenges in measuring nominal GDP, including those involving the digital economy. Finally, we review ongoing work at BLS and BEA to reduce potential biases and further improve measurement.

Suggested Citation

  • Erica L. Groshen & Brian C. Moyer & Ana M. Aizcorbe & Ralph Bradley & David M. Friedman, 2017. "How Government Statistics Adjust for Potential Biases from Quality Change and New Goods in an Age of Digital Technologies: A View from the Trenches," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 187-210, Spring.
  • Handle: RePEc:aea:jecper:v:31:y:2017:i:2:p:187-210
    Note: DOI: 10.1257/jep.31.2.187
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    References listed on IDEAS

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    2. Oulton, Nicholas, 2018. "GDP and the system of national accounts: past, present and future," LSE Research Online Documents on Economics 87178, London School of Economics and Political Science, LSE Library.
    3. Diewert, Erwin & Fox, Kevin J., 2019. "Productivity Indexes and National Statistics: Theory, Methods and Challenges," Microeconomics.ca working papers erwin_diewert-2019-8, Vancouver School of Economics, revised 25 Apr 2019.
    4. Mo Abdirahman & Diane Coyle & Richard Heys & Will Stewart, 2020. "A Comparison of Deflators for Telecommunications Services Output," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Études Économiques (INSEE), issue 517-518-5, pages 103-122.
    5. Niebel, Thomas, 2019. "Wachstumsperspektiven der digitalen Transformation: Wird der ökonomische Mehrwert der Digitalisierung in der Volkswirtschaftlichen Gesamtrechnung angemessen abgebildet?," Working Paper Forschungsförderung 142, Hans-Böckler-Stiftung, Düsseldorf.
    6. Diewert, Erwin & FOX, Kevin J. Fox & SCHREYER, Paul, 2017. "The Digital Economy, New Products and Consumer Welfare," Microeconomics.ca working papers erwin_diewert-2017-12, Vancouver School of Economics, revised 14 Dec 2017.
    7. Watanabe, Chihiro & Tou, Yuji & Neittaanmäki, Pekka, 2018. "A new paradox of the digital economy - Structural sources of the limitation of GDP statistics," Technology in Society, Elsevier, vol. 55(C), pages 9-23.
    8. Brynjolfsson, Erik & Collis, Avinash & Diewert, Erwin & Eggers, Felix & FOX, Kevin J., 2019. "GDP-B: Accounting for the Value of New and Free Goods in the Digital Economy," Microeconomics.ca working papers erwin_diewert-2019-6, Vancouver School of Economics, revised 27 Mar 2019.
    9. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    10. Richard Schmalensee, 2018. "Puzzles and Surprises in Employment and Productivity in U.S. Manufacturing After the Great Recession," International Productivity Monitor, Centre for the Study of Living Standards, vol. 35, pages 5-27, Fall.
    11. Anna M. Stansbury & Lawrence H. Summers, 2017. "Productivity and Pay: Is the link broken?," NBER Working Papers 24165, National Bureau of Economic Research, Inc.
    12. Thomas von Brasch & Diana-Cristina Iancu & Arvid Raknerud, 2018. "Productivity growth, firm turnover and new varieties," Discussion Papers 872, Statistics Norway, Research Department.
    13. Jakub Rybacki & Tamara Bińczak & Filip Kaczmarek, 2018. "Is HICP really harmonized? Problems with quality adjustments and new products," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 97-116.
    14. Thomas von Brasch & Arvid Raknerud & Diana-Cristina Iancu, 2018. "Productivity growth, firm turnover and new varieties," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2018-11, Economic Statistics Centre of Excellence (ESCoE).
    15. Leonard I. Nakamura, 2020. "Evidence of Accelerating Mismeasurement of Growth and Inflation in the U.S. in the 21st Century," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-15, Economic Statistics Centre of Excellence (ESCoE).
    16. Daniel Melser, 2019. "Valuing the quantity and quality of product variety to consumers," Empirical Economics, Springer, vol. 57(6), pages 2107-2128, December.
    17. Shane Greenstein, 2020. "The Basic Economics of Internet Infrastructure," Journal of Economic Perspectives, American Economic Association, vol. 34(2), pages 192-214, Spring.

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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production

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