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The Role of Hedonic Methods in Measuring Real GDP in the United States

Author

Listed:
  • David Wasshausen
  • Brent R. Moulton

    (Bureau of Economic Analysis)

Abstract

Accurate price indexes are crucial for preparing accurate estimates of real gross domestic product and corresponding productivity measures. The price index must capture price change for a ‘relevant’ market basket goods, while at the same time controlling for changes in characteristics and/or quality of these goods. Traditional price indexes (i.e. ‘matched model’) are well suited to capturing price change for goods that exhibit little or no quality change over time, however, for products whose characteristics and/or quality are changing rapidly (e.g. ICT goods), hedonic methods may be more suitable. This paper provides a brief history of hedonic methods employed by U.S. statistical agencies and specifically examines the role of hedonic price indexes in the U.S. National Income and Product Accounts. It also attempts to dispel some popular misconceptions about hedonic methods.

Suggested Citation

  • David Wasshausen & Brent R. Moulton, 2006. "The Role of Hedonic Methods in Measuring Real GDP in the United States," BEA Papers 0067, Bureau of Economic Analysis.
    • Handle: RePEc:bea:papers:0067
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    File URL: https://www.bea.gov/papers/pdf/hedonicGDP.pdf
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    References listed on IDEAS

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    1. Feenstra, Robert C, 1995. "Exact Hedonic Price Indexes," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 634-653, November.
    2. Mick Silver & Saeed Heravi, 2003. "The Measurement of Quality-Adjusted Price Changes," NBER Chapters,in: Scanner Data and Price Indexes, pages 277-316 National Bureau of Economic Research, Inc.
    3. Katharine G. Abraham & John S. Greenlees & Brent R. Moulton, 1998. "Working to Improve the Consumer Price Index," Journal of Economic Perspectives, American Economic Association, vol. 12(1), pages 27-36, Winter.
    4. Randolph, William C, 1988. "Housing Depreciation and Aging Bias in the Consumer Price Index," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(3), pages 359-371, July.
    5. Robert P. Parker & Bruce T. Grimm, 2000. "Recognition of Business and Government Expenditures for Software as Investment: Methodology and Quantitative Impacts, 1959-98," BEA Papers 0002, Bureau of Economic Analysis.
    6. Paul E. Pieper, 1991. "The Measurement of Construction Prices: Retrospect and Prospect," NBER Chapters,in: Fifty Years of Economic Measurement: The Jubilee of the Conference on Research in Income and Wealth, pages 239-272 National Bureau of Economic Research, Inc.
    7. Robert Gillingham, 1975. "Place to Place Rent Comparisons," NBER Chapters,in: Annals of Economic and Social Measurement, Volume 4, number 1, pages 153-178 National Bureau of Economic Research, Inc.
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    Cited by:

    1. David M. Byrne & Stephen D. Oliner & Daniel E. Sichel, 2013. "Is the Information Technology Revolution Over?," International Productivity Monitor, Centre for the Study of Living Standards, vol. 25, pages 20-36, Spring.
    2. Dominik Filipiak & Agata Filipowska, 2016. "Towards data oriented analysis of the art market: survey and outlook," "e-Finanse", University of Information Technology and Management, Institute of Financial Research and Analysis, vol. 12(1), pages 21-31, June.
    3. Unel, Bulent, 2010. "Analyzing skilled and unskilled labor efficiencies in the US," Journal of Macroeconomics, Elsevier, vol. 32(4), pages 957-967, December.
    4. Marta Arespa & Diego Gruber, 2016. "Product Quality and International Price Dynamics," UB Economics Working Papers 2016/340, Universitat de Barcelona, Facultat d'Economia i Empresa, UB Economics.
    5. repec:aei:rpaper:37301 is not listed on IDEAS

    More about this item

    JEL classification:

    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

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