Abstract

The US-China trade disputes and technology war are not only bilateral issues. Rather, they emerge as material external risk and uncertainty impacting the economy of all the other countries. It is time to study the two nations' internal and external policies for taking the lead in new information and communications technologies (ICTs) as well as the subsequent impact on the local economy and identify relevant policy measures.
This study intends to look at the current status of the US-China hegemonic competition and the foreign investment restrictions that followed; to review the literature to identify the spreading path of the hegemonic competition for technology; and finally to carry out a quantitative panel regression analysis to measure the impact the hegemonic competition in new ICT sectors has on the local industry’s total factor productivity.
Specifically, the paper analyzes the direct and indirect impact on the total factor productivity of the local ICT industry that may be caused by the restriction in the movement of physical and human resources, following global value chain (GVC) restructuring and investment restrictions driven by the hegemonic competition for technology. In theory, both positive and negative effects may be driven in various channels depending on the conditions of the respective countries, which necessitates an empirical study.
The paper uses upstream and downstream GVC participation rate and sensitivity by industry, and FDI (value and number of companies) as variables to measure GVC restructuring and investment restrictive measures, and builds industry-level panel data. To calculate industry average total factor productivity, an unobservable variable, company-level productivity is estimated using Statistics Korea's 'business activities survey' data from 2006 through 2018 deploying the method suggested by Ackerberg et al. (2015). Since the impact GVC participation and FDI have on industry productivity may be different depending on the industry's technological capabilities, industry-level IPRs and R&D investments are also included as interaction factors to implement the static and dynamic model.
In the static model, the GVC participation rate, sensitivity to external demand, and FDI value show a positive correlation with industry productivity. Namely, the higher the GVC participation rate, the sensitivity to external demand, and the value of FDI, the higher the industry productivity. Robustness is maintained against the productivity estimation and the dynamic model.
Meanwhile, the higher the R&D investment rate of the industry, the lower the sensitivity to external demand and the effect of having overseas operations. Thus, it is suggested that if GVC is restructured in a way that lowers the overseas-driven added value, the level of industrial productivity degradation may be controlled through increasing domestic R&D. The negative effect materialized in the number of companies operating overseas may also be mitigated through R&D investment.
As suggested by the empirical analysis, R&D investment can influence productivity through indirect channels of GVC and FDI in addition to the direct path. From a policy perspective, when responding to hegemonic competition for ICTs, R&D is well worth being used as a policy tool. Alternatively, existing literature proposes reshoring and GVC diversification, among others. These measures are too long-term, however, to respond to a rapidly-changing global environment.