IDEAS home Printed from https://ideas.repec.org/p/eti/dpaper/20006.html
   My bibliography  Save this paper

Impact of R&D Activities on Pricing Behaviors with Product Turnover

Author

Listed:
  • Yasushi HARA
  • Akiyuki TONOGI
  • Konomi TONOGI

Abstract

This study empirically investigates the impact of research and development (R&D) activity on product turnover based on Point-of-Sales (POS) data. When measuring the inflation rate in an economy, the effects of quantitative, qualitative and volume changes must be isolated from changes in nominal sales figures. Changes in quality can be attributed to corporate R&D activities. In order to examine the effect of R&D activities on price changes in sales data, we construct a unique dataset by combining three datasets: weekly POS data, patent database (IIP Patent DB) data, and the Survey of Research and Development data. We use regression analysis with pooling and panel regression. We observe that while R&D activity may have a causal effect on price increases, a negative effect on the price of incumbent products is also observed. In addition, the relative prices of new and incumbent products tended to be higher for companies with active R&D expenditures. We suggest that continuous R&D is necessary to keep introducing high value products that place upward pressure on prices.

Suggested Citation

  • Yasushi HARA & Akiyuki TONOGI & Konomi TONOGI, 2020. "Impact of R&D Activities on Pricing Behaviors with Product Turnover," Discussion papers 20006, Research Institute of Economy, Trade and Industry (RIETI).
    • Handle: RePEc:eti:dpaper:20006
    as

    Download full text from publisher

    File URL: https://www.rieti.go.jp/jp/publications/dp/20e006.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feenstra, Robert C, 1994. "New Product Varieties and the Measurement of International Prices," American Economic Review, American Economic Association, vol. 84(1), pages 157-177, March.
    2. Kenta IKEUCHI & Kazuyuki MOTOHASHI & Ryuichi TAMURA & Naotoshi TSUKADA, 2017. "Measuring Science Intensity of Industry using Linked Dataset of Science, Technology and Industry," Discussion papers 17056, Research Institute of Economy, Trade and Industry (RIETI).
    3. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Introduction to "Scanner Data and Price Indexes"," NBER Chapters, in: Scanner Data and Price Indexes, pages 1-13, National Bureau of Economic Research, Inc.
    4. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    5. YAMAGUCHI, Shotaro & 山口, 翔太郎 & NITTA, Ryuji & HARA, Yasushi & SHIMIZU, Hiroshi & 清水, 洋, 2018. "Staying Young at Heart or Wisdom of Age: Longitudinal Analysis of Age and Performance in US and Japanese Firms," IIR Working Paper 18-41, Institute of Innovation Research, Hitotsubashi University.
    6. Abe, Naohito & Inakura, Noriko & Tonogi, Akiyuki, 2017. "Effects of the Entry and Exit of Products on Price Indexes," RCESR Discussion Paper Series DP17-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    7. Robert C. Feenstra & Matthew D. Shapiro, 2003. "Scanner Data and Price Indexes," NBER Books, National Bureau of Economic Research, Inc, number feen03-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yasushi Hara & Akiyuki Tonogi & Konomi Tonogi, 2019. "Impact of R&D Activities on Pricing Behaviors with Product Turnover," Working Papers hal-02318466, HAL.
    2. Diewert, W. Erwin & Fox, Kevin J., 2017. "Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data," Microeconomics.ca working papers erwin_diewert-2017-3, Vancouver School of Economics, revised 23 Mar 2017.
    3. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2016. "Product Turnover and Deflation: Evidence from Japan," UTokyo Price Project Working Paper Series 073, University of Tokyo, Graduate School of Economics.
    4. Abe, Naohito & Inakura, Noriko & Tonogi, Akiyuki, 2017. "Effects of the Entry and Exit of Products on Price Indexes," RCESR Discussion Paper Series DP17-2, Research Center for Economic and Social Risks, Institute of Economic Research, Hitotsubashi University.
    5. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2018. "Product Turnover and the Cost of Living Index: Quality vs. Fashion Effects," Globalization Institute Working Papers 337, Federal Reserve Bank of Dallas.
    6. Kota Watanabe & Tsutomu Watanabe, 2014. "Estimating Daily Inflation Using Scanner Data: A Progress Report," UTokyo Price Project Working Paper Series 020, University of Tokyo, Graduate School of Economics.
    7. Qingxiao Li & Metin Çakır, 2024. "Estimating SNAP purchasing power and its effect on participation," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 779-804, March.
    8. Olivier Coibion & Yuriy Gorodnichenko & Gee Hee Hong, 2015. "The Cyclicality of Sales, Regular and Effective Prices: Business Cycle and Policy Implications," American Economic Review, American Economic Association, vol. 105(3), pages 993-1029, March.
    9. Christian Broda & David E. Weinstein, 2010. "Product Creation and Destruction: Evidence and Price Implications," American Economic Review, American Economic Association, vol. 100(3), pages 691-723, June.
    10. Alan Heston, 2017. "Flaw of One Price; The International Comparison Program in Historical Perspective," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 7-21, March.
    11. Kozo Ueda & Kota Watanabe & Tsutomu Watanabe, 2020. "Consumer Inventory and the Cost of Living Index: Theory and Some Evidence from Japan," Working Papers on Central Bank Communication 025, University of Tokyo, Graduate School of Economics.
    12. Gormsen, Christian, 2009. "Intransparent Markets and Intra-Industry Trade," Working Papers 09-20, University of Aarhus, Aarhus School of Business, Department of Economics.
    13. Adam Copeland, 2013. "Seasonality, consumer heterogeneity and price indexes: the case of prepackaged software," Journal of Productivity Analysis, Springer, vol. 39(1), pages 47-59, February.
    14. Kevin J, Fox. & Iqbal A. Syed, 2016. "Price Discounts and the Measurement of Inflation: Further Results," Discussion Papers 2016-05, School of Economics, The University of New South Wales.
    15. Christian Gormsen, 2012. "Intransparent Markets and Intra-Industry Trade," Post-Print halshs-00678264, HAL.
    16. W. Erwin Diewert & Robert C. Feenstra, 2021. "Estimating the Benefits of New Products," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 437-473, National Bureau of Economic Research, Inc.
    17. Kota Watanabe & Tsutomu Watanabe, 2014. "We construct a Törnqvist daily price index using Japanese point of sale (POS) scannerdata spanning from 1988 to 2013. We find the following. First, the POS based inflation rate tends to be about 0.5 ," CARF F-Series CARF-F-342, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    18. James Albrecht & Fabien Postel‐Vinay & Susan Vroman, 2013. "An Equilibrium Search Model Of Synchronized Sales," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 473-493, May.
    19. Mark A. Wynne & Diego Rodriguez‐Palenzuela, 2004. "Measurement Bias in the HICP: What do we know and What do we need to know?," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 79-112, February.
    20. Toro-Gonzalez, Daniel & McCluskey, Jill J. & Mittelhammer, Ron, 2014. "Beer Snobs Do Exist: Estimation of Beer Demand by Type," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(2), pages 1-14.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eti:dpaper:20006. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: TANIMOTO, Toko (email available below). General contact details of provider: https://edirc.repec.org/data/rietijp.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.