Analysis of the Determinants of Innovation in Developing Countries: A Vector Auto-regression Approach

Developing countries; Global competitiveness report; Innovation; R&D; Panel vector auto-regression

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Vol. 8 No. 03 (2020)
Economics and Management
March 4, 2020

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Several factors account for innovation output in developed economies as documented in extant literature. The objective of this study is to make a case for a multi-faceted approach to innovation in developing countries. To analyze various factors affecting innovation, a sample of 43 developing countries is taken and the period of study is between 2009 and 2018.  A vector auto-regression model is used in a panel data setting to test the effect of various variables on innovation at country level, a granger causality test is also conducted to determine the causal relationship among these factors that together can spur innovation activities. Findings suggest a strong influence of R&D and government procurement of technology on the advancement of innovation. R&D is largely affected by the quality of research institutions and university-industry collaborative research, thus showing the strength of the effect of these variables on innovation. Scientists and engineers with requisite expertise greatly improve a country’s innovation efforts, however, developing countries do not benefit fully from the economic value of these experts. These results show that an integration of all these factors is a good approach to enhancing innovation in developing economies.