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Innovation and market value: a quantile regression analysis


  • Alex Coad

    () (CES-MATISSE, Univ. Paris 1 and LEM, Sant'Anna School, Pisa)

  • Rekha Rao

    () (LEM, Sant'Anna School, Pisa)


We construct a new database by matching firm-level Compustat data to NBER patent data, for four 2-digit complex technology sectors. Whilst conventional regression estimators show that the stock market does recognise efforts at innovation, quantile regression analysis adds a new dimension to the literature, suggesting that the influence of innovation on market value varies dramatically across the market value distribution. For firms with a low value of Tobin's q, the stock market will barely recognize their attempts to innovate. For firms with the highest values of Tobin''s q, however, their market value is particularly sensitive to innovative activity.

Suggested Citation

  • Alex Coad & Rekha Rao, 2006. "Innovation and market value: a quantile regression analysis," Economics Bulletin, AccessEcon, vol. 15(13), pages 1-10.
  • Handle: RePEc:ebl:ecbull:eb-06o10012

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    References listed on IDEAS

    1. Bronwyn H. Hall & Adam Jaffe & Manuel Trajtenberg, 2005. "Market Value and Patent Citations," RAND Journal of Economics, The RAND Corporation, vol. 36(1), pages 16-38, Spring.
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    6. Zvi Griliches, 1998. "Patent Statistics as Economic Indicators: A Survey," NBER Chapters,in: R&D and Productivity: The Econometric Evidence, pages 287-343 National Bureau of Economic Research, Inc.
    7. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, March.
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    Cited by:

    1. Bartelsman, Eric & Dobbelaere, Sabien & Peters, Bettina, 2013. "Allocation of Human Capital and Innovation at the Frontier: Firm-Level Evidence on Germany and the Netherlands," IZA Discussion Papers 7540, Institute for the Study of Labor (IZA).
    2. Westerberg, Hans Seerar, 2014. "The Return to R&D and Seller-buyer Interactions: A Quantile Regression Approach," Ratio Working Papers 231, The Ratio Institute.
    3. Faïz Gallouj & Paul Windrum, 2009. "Services and services innovation," Journal of Evolutionary Economics, Springer, vol. 19(2), pages 141-148, April.
    4. Montresor, Sandro & Vezzani, Antonio, 2015. "The production function of top R&D investors: Accounting for size and sector heterogeneity with quantile estimations," Research Policy, Elsevier, vol. 44(2), pages 381-393.
    5. Segarra Blasco, Agustí & Teruel Carrizosa, Mercedes, 2008. "Innovation sources and productivity in Catalonian firms: a quantile regression analysis," Working Papers 2072/9259, Universitat Rovira i Virgili, Department of Economics.
    6. Aviral Tiwari, 2013. "Taxation, Economic Growth and Political Stability," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 20(1), pages 49-61, April.
    7. Ming-Chi Chen & Chi-Lu Peng & So-De Shyu & Jhih-Hong Zeng, 2012. "Market States and the Effect on Equity REIT Returns due to Changes in Monetary Policy Stance," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 364-382, August.
    8. Coad, Alex & Segarra, Agustí & Teruel, Mercedes, 2016. "Innovation and firm growth: Does firm age play a role?," Research Policy, Elsevier, vol. 45(2), pages 387-400.
    9. Daria Ciriaci & Pietro Moncada-Paterno-Castello & Peter Voigt, 2012. "Does size or age of innovative firms affect their growth persistence? Evidence from a panel of innovative Spanish firms," JRC Working Papers JRC74052, Joint Research Centre (Seville site).
    10. Martin Falk, 2012. "Quantile estimates of the impact of R&D intensity on firm performance," Small Business Economics, Springer, vol. 39(1), pages 19-37, July.
    11. Uddin, Md Akther & Masih, Mansur, 2016. "War and peace: why is political stability pivotal for economic growth of OIC countries?," MPRA Paper 71678, University Library of Munich, Germany.
    12. repec:eee:ecmode:v:64:y:2017:i:c:p:610-625 is not listed on IDEAS
    13. repec:eee:iburev:v:27:y:2018:i:1:p:269-280 is not listed on IDEAS
    14. Riccardo Leoncini & Alberto Marzucchi & Sandro Montresor & Francesco Rentocchini & Ugo Rizzo, 2016. "‘Better late than never’: a longitudinal quantile regression approach to the interplay between green technology and age for firm growth," SEEDS Working Papers 0616, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised May 2016.
    15. J Doran & G Ryan, 2016. "The effectiveness of R&D and external interaction for innovation: Insights from quantile regression," Economic Issues Journal Articles, Economic Issues, vol. 21(1), pages 47-65, March.
    16. Daria Ciriaci & Pietro Moncada-Paternò-Castello & Peter Voigt, 2016. "Innovation and job creation: a sustainable relation?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 189-213, August.
    17. Silverio Alarcón & Mercedes Sánchez, 2013. "External and Internal R&D, Capital Investment and Business Performance in the Spanish Agri-Food Industry," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 654-675, September.
    18. Yu-Yen Ku & Tze-Yu Yen, 2016. "Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-33, September.
    19. Gallego-Álvarez, Prof. Isabel & Ortas, Prof. Eduardo, 2017. "Corporate environmental sustainability reporting in the context of national cultures: A quantile regression approach," International Business Review, Elsevier, vol. 26(2), pages 337-353.

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    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior


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