Title: Who does (not) want to pay for innovation - the financing gap story revisited.
Other Titles: Who does (not) want to pay for innovation - the financing gap story revisited.
Authors: Binz, Hanna
Issue Date: 25-May-2010
Abstract: This doctoral dissertation focuses on measuring financial constraints for industrial R&D and the identification of firms that face such constraints and hence are potentially not able to pursue their R&D at the desired level. The identification of potentially constrained firms is crucialfor the design of efficient innovation policy schemes. The thesis contributed to previous empirical studies on incentive and financing problemsfor private sector investment in innovation projects. Themain contribution is basically twofold. First, the thesis adds to previous research on that topic by taking into account the heterogeneity of R&D investments. Second, it contributes to earlier research in terms of methodology. In particular, it is attempted to overcome limitations of previous measuring approaches by introducing direct measures of credit market access andeven a direct measures for the financial constraint itself.The first part presents a test for financial constraints on R&D investment and how they differ from capital investment. To identify constraintsin the access to external capital, a credit rating index is employed. The models show that internal constraints, measured by mark-ups, are moredecisive for R&D than for capital investment. For external constraints,a monotonic relationshipbetween the level of constriction and firm size for both types of investment is found. Thus, external constraints turn out to be more binding with decreasing firm size. The second part analyzes financial constraintson R&D, where it is accounted for heterogeneity among investments whichhas been neglected in previous literature. According to economic theory, investments should be distinguished by their degree of uncertainty, e.g. routine R&D versuscutting-edge R&D. Financial constraints should be more binding for cutting-edge R&D than for routine R&D. Using panel data it can be shown thatR&D spending of firms devoting a significant fraction of R&D to cutting-edge projects is curtailed by credit constraints while routine R&Dinvestments are not. This has important policy implications with respect to the distribution of R&D subsidies in the economy. The third part compartmentalizes R&D activities in its components, ‘R’ and ‘D’ as these activities do not only differ in their nature, but also to a large extenttake place sequentially. The results show that ‘R’ investment is more sensitive to the firms’ operating liquidity than ‘D’ indicating that firms have to rely even more on internal funds for financing their research compared to development activities. Moreover, it is found that (basic) research subsidy recipients’ investment is less sensitive to internal liquidity. The fourth part presents an entirely different approach to the identification of financing constraints. In particular, a survey-based measure of financing constraints is derived from a test that comes closer to the 'ideal experiment' for identifying financing constraints as suggested by Hall (2008). This article furthermore introduces the concept of innovation capability into the context of financing constraints. There are two possible theories on how innovative capabilities affect financingconstraints. First, as innovation capabilities are necessary to do innovation, firms with high capabilities should be able to attract funds easier because of the higher expected success of their projects. On the other hand, it can be argued that investors - although they might be aware of the fact that skill is an important success factor of R&D - do not value such skills. In terms of economic theory this means that uncertaintyabout the outcome of innovation projects outweighs the information on skills. The results from this paper suggest the second alternative. Although one could expect firms with high innovative capacity to be less constrained as they should be able to better convince banks and investors because of all the evidence that skill increase success of innovation projects, they are actually more likely to be constrained. This may be due to the increased demand for financing one the one hand, but also due to the fact that banks and investors may still value 'tangible collateral capital' more than something intangible as innovationcapabilities. The conclusions that can be drawn from this dissertation have important implications for innovation policy particularly for economies in which bank financing plays such a crucial role as it does for example in Germany. Firms in Anglo-Saxon 'market-based' economies with developed and liquid stock markets generally rely to a lower extend on bankfinancing compared to firms in 'banking-dominated' financial systems that can be found in continental Europe.Given that even independently of any financial crisis, economic theory and empirical evidence stress the relevance of financing constraints, the problem presumably deteriorates as the current financial crisis will require banks to conduct an even more detailed risk assessment in the future. Systematic risk assessment techniques as within the implementation of the New Basel Capital Accord affect financing of innovation, in particular the screening of innovative firms. As intangible investments like R&D are not reflected in the firms' balance sheets, financial statement-based estimations of firm value and creditworthiness (internal, but alsoexternal ratings) penalize firms that invest in R&D at least in the short-run. A starting point for future research is thus for example how investments in intangible assets such as the outcome from R&D projects, affect banks' risk evaluation and the decision to provide credit. In addition, the rigorous evaluation of existing policy schemes addressing financial constraints appears to be a desirable task for (European) innovationpolicy. Despite the suggested need for government intervention to support financially constrained firms, it should be noted that also governments are not immune against information asymmetry problems either. With respect to project selection within support programmes, it may be that selection committees do not pick those proposals that promise highest social returns or those that are least likely to attract financing at privatesector sources, but those that seem the most feasible or most likely toyield successful outcomes in the not too distant future. As highly basic research projects may score low on selection criteria like 'feasibility' or 'expected economic value', government agents may behave similar as private lenders when it comes to project selection. Hence, itmay happen that very challenging research projects are not awarded a subsidy. For the pattern of innovation project grants by the Flemishgovernment, there is slight evidence that basic research projects are indeed rejected more frequently.For future European innovation policy, it will therefore remain a challenge to find an optimal policy path that balances targeted subsidy and incentive programmes as well as initiatives that pave the way for market based solutions. The latter may even involve the implementation of fundamental ideas such as legal reforms with respect to accounting policies to better position R&D investments vis-à-vis traditional capital investments.
Publication status: published
KU Leuven publication type: TH
Appears in Collections:Department of Managerial Economics, Strategy and Innovation (MSI), Leuven

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