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An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods

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  • Tim Erickson
  • Ariel Pakes

Abstract

The CPI component indices are obtained from comparing price quotes at a given store in different periods. If we omit comparisons from goods in the store in the initial, but not in the comparison, period we generate a selection bias: goods that exit are disproportionately obsolete goods that have falling prices. Building on Pakes (2003), we explain why standard hedonic predictions for second-period prices of exiting goods do not account for this bias. New hedonic methods are derived, shown to have desirable properties, and are applied to three CPI samples where they generate significant selection corrections. (JEL C43, E31)

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  • 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.
    • Handle: RePEc:aea:aecrev:v:101:y:2011:i:5:p:1707-38
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    2. Emi Nakamura & Jón Steinsson & Miao Liu, 2016. "Are Chinese Growth and Inflation Too Smooth? Evidence from Engel Curves," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(3), pages 113-144, July.
    3. Gabriel Ehrlich & John C. Haltiwanger & Ron S. Jarmin & David Johnson & Matthew D. Shapiro, 2020. "Reengineering Key National Economic Indicators," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 25-68, National Bureau of Economic Research, Inc.
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    5. 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.
    6. Gabriel Ehrlich & John Haltiwanger & Ron Jarmin & David Johnson & Ed Olivares & Luke Pardue & Matthew D. Shapiro & Laura Yi Zhao, 2023. "Quality Adjustment at Scale: Hedonic vs. Exact Demand-Based Price Indices," Working Papers 23-26, Center for Economic Studies, U.S. Census Bureau.
    7. Daniel Melser & Iqbal A. Syed, 2016. "Life Cycle Price Trends and Product Replacement: Implications for the Measurement of Inflation," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(3), pages 509-533, September.
    8. Clemens C. Struck, 2017. "On the Interaction of Growth, Trade and International Macroeconomics," Working Papers 201724, School of Economics, University College Dublin.
    9. 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.
    10. 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.
    11. Iqbal A. Syed & Jan De Haan, 2017. "Age, Time, Vintage, And Price Indexes: Measuring The Depreciation Pattern Of Houses," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 580-600, January.
    12. 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.
    13. Ana Aizcorbe & Nicole Nestoriak, 2010. "Price Indexes for Drugs: A Review of the Issues," BEA Working Papers 0050, Bureau of Economic Analysis.
    14. Aizcorbe, Ana & Bridgman, Benjamin & Nalewaik, Jeremy, 2010. "Heterogeneous car buyers: A stylized fact," Economics Letters, Elsevier, vol. 109(1), pages 50-53, October.
    15. Adam Hale Shapiro & Ana Aizcorbe, 2010. "Implications of Consumer Heterogeneity on Price Measures for Technology Goods," BEA Working Papers 0062, Bureau of Economic Analysis.
    16. Marshall Reinsdorf & Robert Yuskavage, 2018. "Offshoring, Sourcing Substitution Bias, and the Measurement of Growth in U.S. Gross Domestic Product and Productivity," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(1), pages 127-146, March.
    17. Laurien Gilbert, 2018. "Gains from Product Variety and the Local Business Cycle," 2018 Meeting Papers 46, Society for Economic Dynamics.
    18. 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).
    19. Adam Copeland & Adam Hale Shapiro, 2010. "The impact of competition on technology adoption: an apples-to-PCs analysis," Staff Reports 462, Federal Reserve Bank of New York.
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    21. Struck, Clemens C., 2022. "Wealth, price levels, and product quality," International Economics, Elsevier, vol. 170(C), pages 32-48.

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    More about this item

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure

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    1. An Experimental Component Index for the CPI: From Annual Computer Data to Monthly Data on Other Goods (AER 2011) in ReplicationWiki

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