The nexus of FDI, R & D, and human capital on Chinese sustainable development: Evidence from a two-step approach

Abstract

This study examines the effect of the foreign direct investment (FDI)-human capital and R & D-human capital interactions (FDIHC and RDHHC) on Chinese development between 1991 and 2015. Based on endogenous growth theory, the study focuses on FDI, R & D, and human capital as important factors for sustained economic growth; the interactions among factors are set as the main variables affecting economic growth (GDP). In particular, this study attempts a two-step empirical analysis. First, data mining and semantic network analysis (SNA) are performed using variables as keywords; reliability and realism are reflected as variables. Second, using the vector error correction model (VECM), the study analyzes short and long run mutual influences between variables. The results show that, in data mining and SNA with FDI and R & D as keywords, words related to human capital show high frequency, centrality, and clustering. This finding implies that FDIHC and RDHHC have robustness as variables and can be used as interaction variables. According to the VECM results, FDIHC and RDHHC have positive influences on GDP in the short and long run. The results of a variance decomposition test show that RDHHC has strong mid- to long-run impacts on GDP, FDIHC, and R & D itself.