Are subsidies called for when adverse selection hinders the financing of innovation?

Investment in innovation is special. More specifically, from the perspective of investment theory, innovation investment has a number of characteristics that make it different from ordinary investment. First and foremost, perhaps most of the R&D portion of such investment is in the wages and salaries of highly educated scientists and engineers. Their efforts create an intangible asset – the firm’s knowledge base – from which profits will flow in future years. To the extent that this knowledge is “tacit” rather than codified, it is embedded in the human capital of the firm’s employees and is therefore lost if they leave or are fired. As emphasized in the literature, this has an important implication for the conduct of R&D investment. Since the resource base of the firm can be critically affected if such workers leave or are laid off, firms tend to smooth their R&D spending over time, in order to avoid having to lay off knowledge workers. Interestingly, this in turn implies that R&D spending at the firm level typically behaves as if it involves high adjustment costs. Two consequences follow, one substantive and one that affects empirical work in this area. First, in equilibrium the required rate of return to R&D may be relatively high simply to cover the adjustment costs. Second, it will be difficult to empirically measure the impact of changes in the costs of capital on such investment, because these effects can be weak in the short run due to the sluggish response of R&D to any changes in its cost.

A second noteworthy feature of R&D investment is the degree and nature of uncertainty associated with its output. Importantly, this uncertainty tends to be greatest at the onset of a research project, which implies that an optimal R&D strategy has an option-like character and really should not be analysed in a static framework. R&D projects with small probabilities of great success in the future may be worth continuing even if they do not pass an expected-return test. The uncertainty here can be extreme, and not a simple instance of a well-specified distribution with finite mean and variance. Actually, there is evidence that the distribution of profits from innovation can take the form of a Pareto distribution, for which the variance does not exist. Consequently, standard risk-adjustment methods will not work well in this case. From the perspective of the financing of investment in innovation, uncertainty has the important characteristic that as investments are made over time, new information arrives, which may modify the uncertainty. This implies that the decision to invest in any particular project is not a once-for-all decision, but needs to be reassessed throughout the life of the project. In addition to making such investment a real option, the sequence of decisions complicates the analysis by introducing dynamic elements into the interaction of financier (within or outside of the firm) and innovator.

These considerations concerning the effects of uncertainty on the financing of innovation projects are of course highly relevant. But equally important are concerns about the effects of asymmetric information about the quality of an innovation project between entrepreneur and financier, which can result in a higher cost of external funds compared to internal capital, and thus create a funding gap. The funding gap can in turn prevent small and new technology-based entrepreneurial firms, in particular, from undertaking economically viable innovation projects. This observation has provided the grounds for government intervention in the form eg of direct subsidies for R&D, aimed at reducing the financing constraints of technology-based start-ups. However, there are relatively few contributions to the theoretical literature that analyse the interaction between financing constraints and R&D subsidies. In a forthcoming Bank of Finland discussion paper "Adverse Selection and Financing of Innovation: Is There Need for R&D Subsidies" Tuomas Takalo and Tanja Tanayama contribute to the existing literature by analysing the effects of an R&D subsidy program implemented by the government under financial constraints generated by asymmetric information.

There is now a vast literature in this area, thanks to Akerlof's famous contribution on the lemons problem, which singles out adverse selection as a major source of financing constraints. Entrepreneurs have better information about the quality of their own projects than do lenders, whose project valuations generally reflect average project quality. This may raise the rate of return required by lenders so high that it becomes unprofitable for an entrepreneur without sufficient internal funding to undertake an economically viable project. As the authors note, the two interrelated solutions to the adverse selection problem that have been proposed are signaling and financial intermediation. That an entrepreneur has a stake in the project could serve as a credible signal of the quality of the project. Reputation may also reduce financing constraints, because over time borrowers who manage to acquire good reputations encounter less severe informational problems. Financial intermediaries such as banks could in turn alleviate financing constraints through information gathering because, relative to atomistic markets, they may have a cost advantage in screening and monitoring loan applicants. In particular, it has been argued that venture capital and related organizations can, through intensive screening and monitoring, overcome informational problems and mitigate capital constraints.

For various reasons – many of which are discussed in detail by Takalo and Tanayama – the proposed solutions may fail to eliminate financing constraints, especially in the case of science and technology-based start-ups. Most of these originate from informational problems that are particularly severe in financing R&D projects, as these projects typically involve soft information that is hard to verify. Facing these problems, governments in several countries have intervened, often via direct R&D subsidies, to reduce financing constraints. Government programs that allocate direct subsidies are based on specific selection schemes, where the selection is accomplished via ex-ante screening of the applications. Takalo and Tanayama, building on Holmstöm and Tirole (1997)¹, develop a model of innovation finance in which capital-constrained entrepreneurs may be able to tap a public agency (in addition to private sources) for funding. They specifically analyse whether R&D subsidy policies can ease financing constraints due to adverse selection. The authors show that under certain circumstances, they can. Interestingly, the effect comes through two channels. First, the subsidy itself reduces capital costs related to innovation projects by reducing the required amount of market-based funding. Second, the observation that an entrepreneur has received a subsidy for an innovation project provides an informative signal to private investors in the market. In effect, Takalo and Tanayama study whether a subsidy by a public agency could act as a certification for an unknown entrepreneur and improve her possibilities to secure funding from private markets. The novelty here seems to be, as the authors rightly emphasize, that the idea of certification by a trusted financial intermediary is rigorously applied to the public funding of corporate R&D. It is now well known from the literature that the effects of subsidies on entrepreneurs' finance under asymmetric information critically depend on the assumed distribution of the project returns. More specifically, adverse selection can generate too much lending instead of financing constraints. Also in the model of Takalo and Tanayma, the beneficial effects of subsidies are more limited if adverse selection generates overinvestment rather than financing constraints. However, as they note, the aforementioned literature abstracts from the signaling role of subsidies as well as from the social benefits of R&D. The paper by Takalo and Tanayama is of great interest in that it provides a new perspective on the effects of public R&D subsidies on the funding of innovation projects. It is also an ingenious application of the Holmsröm-Tirole framework, which has already been applied in a variety of other interesting ways in the area of corporate or entrepreneurial finance. There is still much to learn, not only about the subject matter – the effects of public intervention on the financing of innovation projects – but also about the modeling framework itself. Hence, this line of research should clearly be further pursued.