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Measuring the Aggregate Price Level: Implications For Economic Performance and Policy

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  • Robert J. Gordon

Abstract

Inaccurate measures of the aggregate price level may distort short-run policy decisions and may produce misleading comparisons of productivity growth across decades and among nations. This paper serves a dual purpose of reviewing compactly the vast American literature on price and output measurement, and of identifying special aspects of American methods which affect international comparisons of inflation and output growth. The traditional problem of substitution bias in the Consumer Price Index (CPI) is of minor importance compared with the bias introduced by new products, changes in the quality of existing products, and outlet substitution bias. The quality bias for U.S. consumer durables has recently been estimated to be roughly 1.5 percent per year for the postwar period, and roughly 3 percent per year for consumer durables, The only available study of outlet substitution bias estimates a 2 percent annual rate for food in the 1980s. Cross-country differences in measurement methods tend to overstate the recent productivity performance of U.S. relative to European manufacturing, with an understatement for U.S. nonmanufacturing. Both European and U.S. manufacturing performance are probably understated relative to Japan, which seems to do the best job of incorporating new products and correcting for quality change of high tech goods.

Suggested Citation

  • Robert J. Gordon, 1992. "Measuring the Aggregate Price Level: Implications For Economic Performance and Policy," NBER Working Papers 3969, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:3969
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    References listed on IDEAS

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    1. Ernst R. Berndt & Zvi Griliches, 1993. "Price Indexes for Microcomputers: An Exploratory Study," NBER Chapters, in: Price Measurements and Their Uses, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Harchaoui, Tarek M & Lasserre, Pierre, 2001. "Testing the Option Value Theory of Irreversible Investment," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 141-166, February.
    2. Escobal D'Angelo, Javier & Castillo, Marco, 1994. "Sesgos en la medición de la inflación en contextos inflacionarios: el caso peruano," Working Papers 42246, Group for the Analysis of Development (GRADE).
    3. Luis Fernando Melo Velandia & Franz Hamann Salcedo, 1998. "Inflacion Basica. Una Estimacion Basada En Modelos Var Estructurales," Borradores de Economia 2848, Banco de la Republica.
    4. Michael F. Bryan & Stephen G. Cecchetti, 1993. "The consumer price index as a measure of inflation," Economic Review, Federal Reserve Bank of Cleveland, vol. 29(Q IV), pages 15-24.
    5. Stephen G. Cecchetti, 1997. "Measuring short-run inflation for central bankers," Review, Federal Reserve Bank of St. Louis, issue May, pages 143-155.
    6. Norberto Rodríguez-Niño & Alejandra Ramírez-Ramírez, 2018. "Metodologías semi-estructurales para estimar la Inflación básica mensual en Colombia," Borradores de Economia 1040, Banco de la Republica de Colombia.
    7. Inoue, Tetsuya, 1998. "Impact of Information Technology and Implications for Monetary Policy," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 16(2), pages 29-60, December.

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    More about this item

    JEL classification:

    • 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
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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