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Erschienen in:
Introduction Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

3. Knowledge Intensity and Risk Sharing

verfasst von : T. V. S. Ramamohan Rao

Erschienen in: Risk Sharing, Risk Spreading and Efficient Regulation

Verlag: Springer India

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Abstract

It is often necessary to combine formal knowledge (written down, blueprints) with informal knowledge (rules of thumb and heuristic adaptations required to scale up technology) to “work a patent.” Informal knowledge must be provided by the inventor through his participation. Adverse selection of partners and their personal interests (moral hazard) may create risks. These problems have been highlighted in the context of biotechnology in particular. An attempt has been made to model the sharing of knowledge, costs, and returns. R&D, that creates external effects, is generally entrusted to public scientific organizations and transferred to private firms for its adoption. The similarity of issues is highlighted. The advantages of risk sharing have been juxtaposed with dimensions of risk spreading that they involve.

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Vorheriges Kapitel Conferences and Publications
Nächstes Kapitel Information Asymmetry
Fußnoten
1
In most theoretical models of this nature, the expectation of the expected output does not, or cannot, include all the relevant variables. These omitted variables are the primary source of randomness and variance. If some of them can be identified, but the expected value specification cannot incorporate them by utilizing appropriate economic theory, then their effect must be reflected in endogenous randomness. If they cannot be identified or measured suitably, then they will be the major source of exogenous randomness. Randomness is specified through variance even in situations where the direction of the effect of a variable cannot be predicted a priori.
 
2
In most practical contexts, the royalty rates were shown to be independent of the skill level. For example, Kaufman and Lafontaine (1994, p. 314) observed that a franchise (such as McDonald’s) keeps the sharing fraction constant. From a practical point of view, this enables them to attract only highly skilled franchisees and/or those with a low degree of risk aversion, for the constant royalty rate leaves greater ex ante rents with the franchisees. The existence of such ex ante rents in technology transfer arrangements was noted in Gallini and Wright (1990). A word of caution, however, is in order. The above mentioned studies noted that “efficiency of the agent” is difficult to operationalize and measure. The observed insignificance of the skill level, as a determinant of the royalty rate, may be due to the insufficiency of measurement. This is explicit in Yun (1999, p. 106).
 
3
Sonka and Pueppke (1999) noted that “much of the market application of biotechnology, in general, has involved small, entrepreneurial firms driving innovation. Often, these firms exploited publicly available knowledge to overcome their lack of (skill). Relative to agricultural technology, an important role of publicly supported research may be to create knowledge that can be used to fuel innovation in the market place.”
 
4
Even private firms may encounter financial constraints given the high risks of biotechnology projects. The Government of India (through its organ DBT) created BCIL (Biotechnology Consortium of India) with participation from IDBI, ICICI, and 30 other firms in the public sector. “It stipulated startups, arranged technology transfer and supported their efforts to attract adequate finances.” For details, see Ramani (2002). On the other hand, France allowed publicly supported scientists and institutions to become shareholders in the firms associated with their laboratories. They may, as a result of such arrangements, gain control on knowledge leaks and performance of private firms. When the financial constraint is a problem, the scientist may also be allowed to seek venture capital and/or equity financing. However, this will reduce his control to some extent. It may also place a limit on the discoveries that can be moved to the commercial stage due to differences in perceptions about appropriability.
 
5
Note that the cost of licensing to a private firm is km 2 + m 2/2δ. On the other hand, if the scientist creates his own startup, it will be m 2/2δ*. Hence, licensing will be feasible only if δ* < δ/(1 + 2kδ). k will also decrease as more private firms acquire competence either through learning by doing or hiring young scientists who acquired the skills through training and education. k may also decrease as n increases and/or α tends to unity. It should be noted that a private firm may consider σ 2 to be high because they are not sure about the extent and/or efficiency of informal knowledge transfer that they receive. To an extent, therefore, σ 2 may decrease with an increase in k and/or α. An efficient choice of k may also be conceptualized.
 
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Metadaten
Titel
Knowledge Intensity and Risk Sharing
verfasst von
T. V. S. Ramamohan Rao
Copyright-Jahr
2016
Verlag
Springer India
Buch
Risk Sharing, Risk Spreading and Efficient Regulation

Print ISBN: 978-81-322-2561-4

Electronic ISBN: 978-81-322-2562-1

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-81-322-2562-1_3