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A note on approximation of distribution function for the number of innovation activities

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  • Seung-Hoon Yoo

    (Hoseo University
    Hoseo University)

  • Hye-Seon Moon

    (Carnegie Mellon University)

Abstract

This note attempts to approximate the distribution function for the number of innovation activities (NIA) in the manufacturing sector using the dataset of 2002 Korean Innovation Survey. The mixture model applied here can easily capture the bimodality feature of the NIA distribution and provide some useful information such as the mean of NIA and the effect of a firm’s characteristic on whether the firm will undertake innovation activity.

Suggested Citation

  • Seung-Hoon Yoo & Hye-Seon Moon, 2008. "A note on approximation of distribution function for the number of innovation activities," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(3), pages 445-452, December.
    • Handle: RePEc:spr:scient:v:77:y:2008:i:3:d:10.1007_s11192-008-1802-8
    DOI: 10.1007/s11192-008-1802-8
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    References listed on IDEAS

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    1. Seung-Hoon Yoo, 2004. "A Note on an Approximation of the Mobile Communications Expenditures Distribution Function Using a Mixture Model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 747-752.
    2. Morduch, Jonathan J. & Stern, Hal S., 1997. "Using mixture models to detect sex bias in health outcomes in Bangladesh," Journal of Econometrics, Elsevier, vol. 77(1), pages 259-276, March.
    3. Becker, Wolfgang & Dietz, Jurgen, 2004. "R&D cooperation and innovation activities of firms--evidence for the German manufacturing industry," Research Policy, Elsevier, vol. 33(2), pages 209-223, March.
    4. Krinsky, Itzhak & Robb, A Leslie, 1986. "On Approximating the Statistical Properties of Elasticities," The Review of Economics and Statistics, MIT Press, vol. 68(4), pages 715-719, November.
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