earticle

영어

Based on the CDM model, this paper empirically examines the links of R&D, innovation, and labor productivity using Korean Community Innovation Survey (KCIS) for manufacturing firms over the period 2013 to 2015. Estimating the model, I attempt to alleviate two major econometric problems such as endogeneity for the variables and sample selection biases caused by distribution problems of R&D spending and technological innovations. To do this, I control the former bias by employing sequential instrumental variable estimation procedures, and the latter by using both the Generalized Tobit model and the bivariate probit estimation technique. Main empirical findings in the paper can be summarized as follows. First of all, this paper found that the separate estimation of the structural CDM model should lead to biased results due to ignoring sample selection and endogeneity problems. This evidence confirms validity of using botht the bivariate probit model and the type II Tobit model. Second, the results show that R&D expenditure should be positively associated with enhancement of product innovation, rather than process innovation. This implies that government R&D support can have a stronger effect on encouraging product innovation through an increase in R&D investment in SMEs. Third, the innovation protection methods, both legal and strategic, are found to have a positive effect on R&D investment but no effect on R&D intensity. In the innovation output models, on the other hand, only strategic protection method can have a positive effect on both product and process innovations. Fourth, the firm size proxied by the number of workers is found to be negatively related to the R&D investment. As the size of firms grows, the probability of R&D investment is higher, but per worker R&D investment is smaller. This evidence supports Scherer’s hypothesis that innovation activities are more active of small-medium firms in the competitive markets, rather than in the monopoly market suggested by Schumpeter. Fifth, the results show that information flow from suppliers and customers plays an important role as source of knowledge for invention and innovation. In the knowledge production function or the innovation output model, the flow has a positive effect on both the product and process innovation. However, information flow from competitors is found to affect process innovation, but it is not useful to develop new products. Next, the estimated coefficients for government financial support are found to be statistically significant in both the R&D investment decision and the R&D intensity models. This implies that the government financial support can have crowding-in effects on R&D investment, rather than crowding-out effects, and thus it could lead to an enhancement of R&D investment in SMEs. Finally, the results show that the estimated coefficients of the predicted values for product innovation are statistically significant in the labor productivity model, implying that product innovation should have a positive effect on labor productivity and thus eventually affect economic growth positively. This results also confirms existence of endogeneity problem with product innovation, not with process innovation.