Study on the Complementarity Effect according to the Overlapped, Repetitive and Sequential Support in Innovation Policy

Abstract

Innovation activity is an important factor in firms growth, and the government has implemented various policies that support the firms innovation activity. There are various rationales for public policy implementations that encourage firms innovation activity

first, there is the presence of innovation spillover. If innovation activity is only dependent on the private sector, it causes a lower level of innovation than the social optimum. To solve this problem, the public sector, particularly the government, needs to support firms innovation activity. The other problem is asymmetric information in the loan market, known as the Lemon market problem. Due to asymmetric information in the loan market, the marginal costs of capital increases. This makes outside investors reduce their investments in firms innovation activities. Because of the spillover effect and Lemon market problem, firms can fail to manage their innovation activity. Therefore, the government should intervene in the market, and resolve these asymmetric information problems and the uncertainty of the capital market. With government intervention, firms can continue focusing their efforts on innovation activities and increasing their capacities. Alongside the implementation of various government policies, discussions regarding evaluations of public policy have been consistently undertaken in economics, because it is very important to evaluate whether public policies have played a proper role there. These studies on the evaluation of public policy not only include evaluations of a single policy, but also the discussion about which policies can play more effective roles in certain situations. However, all policies have direct or indirect connections with each other, so they cannot be discriminative or exclusive. Consequently, in order to evaluate one policy correctly, its interactions with other policies also require consideration. However, studies on the interactions in innovation policies—that is, studies on cases where many policies have been simultaneously implemented—are insufficient . These interactions and their complementarity effects are quite important factors in real situations, but have not been discussed sufficiently in innovation policy. This paper is focused on these interactions and the complementarity effects of innovation policy. For the analysis, a theoretical framework about interaction and complementarity effects will be suggested based on previous economic concepts. Along with the suggested theoretical framework, various analyses will be conducted in this paper, and various policy implications will be deduced. Various methodologies for estimating impact assessments of public policy have been discussed in previous economic studies. Among these methods, a matching estimator is used in this paper, because it is the most suitable method for estimating the complementarity effect. In particular, in this paper, the multivariate matching estimator considering the propensity score has been applied to reduce the selection bias that can occur in impact assessment studies. The main results of this paper are the following: The complementarity effect of overlapped support in innovation policy is positive when heterogeneous policies are overlapped

however, in the case of overlapping homogeneous policies, the complementarity effect is negative. Therefore, policy makers have to consider policies that have been given to the firm before supporting any new policies, and it is desirable that supporting homogeneous policies to the same firms is avoided. Second, in the analysis of the effects of repetitive support, firms receiving repetitive support perform better than firms that do not receiving such support. Repetitive support is when the same policies are supported continuously

however, as the number of repetition increases, the marginal effect may stagnate or diminish. That is to say, in public policy, the continuity of support plays an important role in the growth of firms, but excessive repetition can be inefficient in a firms' growth. Therefore, when policy makers select the firms to receive support, they need to consider these characteristics of innovation policy. Finally, the complementarity effect of sequential support in innovation policy is analyzed. Sequential support means that different policies are supported sequentially. In this case, the firms that receive sequential support are superior to firms that receive single support, in terms of their financing and capacity for innovation. This result means that if different policies are well mixed, their effect can be larger than that of a single policy. Therefore, when the policy makers choose the firms that receive policy support, they need to consider the path dependency of the policies of each firm. Compared with previous studies, this paper has some uniqueness in the following way: First, deviating from the view of previous studies that focused on the evaluation of a single policy, this paper has considered interactions and the complementarity effect of innovation policy through "policy mix," an economic term. Based on these concepts, this paper suggests an analysis framework for the analysis of interactions and the complementarity effect of innovation policy. Second, by examining the various methodologies for the evaluation of government support, the most suitable method for estimating the complementarity effect has been developed in this paper. Finally, through various application analyses in the case of overlapped support, repetitive support, and sequential support, this paper suggests varied policy implication to the policy makers.