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Innovative Capability and Financing Constraints for Innovation: More Money, More Innovation?

ZEW Discussion paper
Authors: Hottenrott, Hanna; Peters, Bettina;

Innovative Capability and Financing Constraints for Innovation: More Money, More Innovation?

Abstract

Economic theory suggests that financing constraints may occur due to capital market imperfections. These particularly affect investments in innovation projects as such projects are typically characterized by a high degree of uncertainty, complexity and specificity. Financing innovation externally is thus likely to be more costly compared to financing of other investment. Hence, internal sources of financing are crucial for the implementation of innovation projects. However, internal funds are not inexhaustible either. They are naturally limited and raising new equity may be costly and often undesired. Financing constraints, however, may not affect all firms to the same extent. This paper addresses the question of which firms face financing constraints. Such identification is particularly interesting for policy makers in order to design effective policy schemes as financing constraints lead to a suboptimal level of investment in innovation. In contrast to previous empirical studies, our analysis is based on the idea of an ideal test for identifying financial constraints on investment in innovation as proposed by Hall (2008). She suggests that 'the ideal experiment for identifying the effects of liquidity constraints on investment is to give firms additional cash exogenously, and observe whether they pass it on to shareholders or use it for investment and/or R&D. [...] If they choose the second [alternative], then the firm must have had some unexploited investment opportunities that were not profitable using more costly external finance'. That is, these firms have been financially constrained. This study contributes to the literature in the following three main aspects. First, we employ a direct indicator derived from survey information in which firms were offered a hypothetical cash payment. Second, we account for the firm's choice between alternatives of use for the money. Third, we introduce the concept of innovative capability and how it affects financing constraints for innovation. The results from our econometric analysis show that financial constraints for innovation do not depend on the availability of funds per se, but are driven by innovative capability through increasing resource requirements. That is, firms with high innovative capability but low financial resources are more likely constrained than others. Yet, we also observe constraints for financially sound firms that may have to put some of their ideas on the shelf. Firms with low innovative capability choose other options, such as investment in physical capital. Taking account of all options for usage of the additional money, we further find in contrast to the innovation decision, the decision to serve debt is to a large extent driven by the financial background. Firms with low internal funds or a bad credit rating would primarily repay debt instead of investing additional cash in innovation projects.

Countries
Germany, Belgium
Keywords

330, Innovation,financing constraints,innovative capability,multivariate probit models, innovation,financing constraints,innovative capability,multivariate probit models, financing constraints, innovative capability, multivariate probit models, innovation, financing constraints, innovative capability, multivariate probit models, C35, Verschuldungsrestriktion, Innovation, Deutschland, Risikokapital, O31, O32, ddc:330, innovation, Probit-Modell, Forschungsfinanzierung, Schätzung, jel: jel:C35, jel: jel:O31, jel: jel:O32

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    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    278
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
278
Top 0.1%
Top 1%
Top 10%
Green
bronze