The Effect of Inward and Outward Foreign Direct Investment o n Regional Innovation Performance: Evidence from China
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Purpose: This study examines how IFDI (Inward FDI) and OFDI (Outward FDI) of China affect the regional innovation performance using a panel data of Chinese provinces and municipalities. Design/methodology/approach: We use the system Generalized Method of Moments(GMM) estimation method to correct for the endogeneity of the dependent variable. A balanced panel data set of 30 provinces and municipalities in China over the period 2003- 2017 is employed in the analysis. We measure the regional innovation performance on two scales: the number of patent grants per 10,000 inhabitants and new product sales. Findings: The empirical results show that IFDI and OFDI have significantly positive impact on innovation performance and that the impact of IFDI is bigger than that of OFDI in new product sales. We also identify three positive variables- R&D intensity, absorptive capacity, and GDP growth, while the other variables cannot be concluded because of their different signs depending on the model. Research limitations/implications: This research is not without limitations. First, this study failed to take account of the overseas destination and the motives of OFDI due to the data limitations. Considering these factors may produce different results. Second, this study considered only high-tech industry in calculating the industrial specialization and diversification index because of the data limitations. Expanding the scope of the industry would result in different values of the indices, and thus our empirical results would be changed accordingly. Originality/value: Firstly, we provide evidence for the potential positive impact of OFDI and IFDI on regional innovation performance for the extended period until 2017. China’s OFDI rose significantly during the second decade of the 21st century. So it was necessary to conduct a research on the extended period. Secondly, we do not include OFDI and IFDI as independent variables in the same equation, but use them separately in different equations because the inclusion of them in the same equation raises the concern of potential multicollinearity as China’s OFDI and IFDI have a very high correlation, which is also what is different from preceding studies.
Abstract
Purpose: This study examines how IFDI (Inward FDI) and OFDI (Outward FDI) of China affect the regional innovation performance using a panel data of Chinese provinces and municipalities. Design/methodology/approach: We use the system Generalized Method of Moments(GMM) estimation method to correct for the endogeneity of the dependent variable. A balanced panel data set of 30 provinces and municipalities in China over the period 2003- 2017 is employed in the analysis. We measure the regional innovation performance on two scales: the number of patent grants per 10,000 inhabitants and new product sales. Findings: The empirical results show that IFDI and OFDI have significantly positive impact on innovation performance and that the impact of IFDI is bigger than that of OFDI in new product sales. We also identify three positive variables- R&D intensity, absorptive capacity, and GDP growth, while the other variables cannot be concluded because of their different signs depending on the model. Research limitations/implications: This research is not without limitations. First, this study failed to take account of the overseas destination and the motives of OFDI due to the data limitations. Considering these factors may produce different results. Second, this study considered only high-tech industry in calculating the industrial specialization and diversification index because of the data limitations. Expanding the scope of the industry would result in different values of the indices, and thus our empirical results would be changed accordingly. Originality/value: Firstly, we provide evidence for the potential positive impact of OFDI and IFDI on regional innovation performance for the extended period until 2017. China’s OFDI rose significantly during the second decade of the 21st century. So it was necessary to conduct a research on the extended period. Secondly, we do not include OFDI and IFDI as independent variables in the same equation, but use them separately in different equations because the inclusion of them in the same equation raises the concern of potential multicollinearity as China’s OFDI and IFDI have a very high correlation, which is also what is different from preceding studies.
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