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Nonparametric quantile regression analysis of R&D-sales relationship for Korean firms

Author

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  • Joon-Woo Nahm

    (Department of Economics, Sogang University, C.P.O. Box 1142, Seoul, Korea E-mail: Jnahm@ccs.sogang.ac.kr)

Abstract

This paper applies the nonparametric quantile regression estimation procedure to the analysis of the innovation-firm size relationship using Korean manufacturing firms data. Due to the high asymmetric distribution of R&D expenditure, the mean regression does not capture properly the stylized facts of R&D behavior; hence it underestimates the sales elasticity. Comparing the parametric estimates and nonparametric estimates allows us to see that there exists a nonlinear relationship in innovative activity and sales. Dividing the data into three groups according to the sales volume, the elasticity in the medium-sized firms is the biggest for scientific firms. This result conforms that the findings of Scherer (1965) coincide with findings from Korean manufacturing firms data in the sense that R&D expenditure tends to increase faster than firm size with size up to a point and then more slowly among larger firms. For the non-scientific firms, it steadily increases showing increasing returns to scale in innovative activity in large firms.

Suggested Citation

  • Joon-Woo Nahm, 2001. "Nonparametric quantile regression analysis of R&D-sales relationship for Korean firms," Empirical Economics, Springer, vol. 26(1), pages 259-270.
  • Handle: RePEc:spr:empeco:v:26:y:2001:i:1:p:259-270
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    Citations

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    Cited by:

    1. Matthew Spiegel & Heather Tookes, 2008. "Dynamic Competition, Innovation and Strategic Financing," Yale School of Management Working Papers amz2500, Yale School of Management.
    2. 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.
    3. 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.
    4. Mercedes Teruel & Agustí Segarra, 2011. "Productivity and R&D sources in manufacturing and service firms in Catalonia: a regional approach," ERSA conference papers ersa11p1860, European Regional Science Association.
    5. 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.
    6. Konstantinos Konstantakis & Panayotis G. Michaelides & Theofanis Papageorgiou, 2014. "Sector size, technical change and stability in the USA (1957-2006): a Schumpeterian approach," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 41(10), pages 956-974, October.
    7. Manuel Landajo & Javier De Andrés & Pedro Lorca, 2008. "Measuring firm performance by using linear and non‐parametric quantile regressions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(2), pages 227-250, April.
    8. Degner, Harald, 2010. "Windows of technological opportunity: do technological booms influence the relationship between firm size and innovativeness?," FZID Discussion Papers 15-2010, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    9. Matthew Spiegel & Heather Tookes, 2008. "Dynamic Competition, Innovation and Strategic Financing," Yale School of Management Working Papers amz2500, Yale School of Management.

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