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Quality-Adjusted Price Measurement: A New Approach with Evidence from Semiconductors

Author

Listed:
  • David M. Byrne

    (Federal Reserve Board)

  • Brian K. Kovak

    (Carnegie Mellon University and NBER)

  • Ryan Michaels

    (Federal Reserve Bank of Philadelphia)

Abstract

Many markets exhibit price dispersion across suppliers of observationally identical goods. Statistical agencies typically assume this dispersion reflects unobserved quality, so standard price indexes do not incorporate price declines when buyers substitute toward lower-price suppliers. We show that long-run price differences across suppliers can be used to infer unobserved quality differences and propose an index that accommodates quality-adjusted price dispersion. Using transaction-level data on contract semiconductor manufacturing, we document substantial quality-adjusted price dispersion and confirm that a standard index is biased above our proposed index.

Suggested Citation

  • David M. Byrne & Brian K. Kovak & Ryan Michaels, 2017. "Quality-Adjusted Price Measurement: A New Approach with Evidence from Semiconductors," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 330-342, May.
    • Handle: RePEc:tpr:restat:v:99:y:2017:i:2:p:330-342
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    File URL: http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00640
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    Citations

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    Cited by:

    1. Florencia Melisa Fares & Guido Zack & Ricardo Gabriel Martínez, 2020. "Sectoral Price and Quantity Indexes of Argentine Foreign Trade," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 93, pages 297-328, Julio-Dic.
    2. 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.
    3. Yuriy Gorodnichenko & Oleksandr Talavera & Nam Vu, 2020. "Quality of Goods and Price Setting for CPUs," Discussion Papers 20-23, Department of Economics, University of Birmingham.
    4. Kenneth Flamm, 2019. "Measuring Moore’s Law: Evidence from Price, Cost, and Quality Indexes," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 403-470, National Bureau of Economic Research, Inc.
    5. Ana M. Aizcorbe & Jeff Chen, 2022. "Outlet Substitution Bias Estimates for Ride Sharing and Taxi Rides in New York City," BEA Working Papers 0192, Bureau of Economic Analysis.
    6. Ana Aizcorbe & Jeffrey C. Chen, 2023. "Outlet Substitution Bias Estimates for Ride Sharing and Taxi Rides in New York City," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2023-02, Economic Statistics Centre of Excellence (ESCoE).
    7. Kenneth Flamm, 2018. "Measuring Moore’s Law: Evidence from Price, Cost, and Quality Indexes," NBER Working Papers 24553, National Bureau of Economic Research, Inc.
    8. Gorodnichenko, Yuriy & Talavera, Oleksandr & Vu, Nam, 2021. "Quality and price setting of high-tech goods," Economic Modelling, Elsevier, vol. 98(C), pages 69-85.
    9. repec:wsr:wpaper:y:2018:i:185 is not listed on IDEAS

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