Econometric study of the impact of technology and innovation on economic growth

The impact of technological innovations on economic growth is of interest to policy makers and economists. With the emergence of the Fourth Industrial Revolution, interest in technological innovations is increasing. It has become an important issue for countries to generate technological innovations, to ensure the continuity of this innovation production and to transform innovations into economic growth. Many of econmists agree that technological innovations are the cause of economic growth. However, the main discussion in the literature is based on methods of generating technological innovations. In this study, the relationships between gross domestic product, number of triadic patents and total expenditures on R&D are analyzed using panel data analysis methods. Triadic patent refers to patents obtained from three different patent centers: Japan Patent Office, European Union Patent Office and United States Patent and Trademark office. Triadic patents are thought to better show patents for inventions that can be commercially profitable. Therefore, triadic patent numbers are used in this study. In the study, it was examined whether the number of triadic patents and the total expenditure on R&D led to economic growth. In addition, the factors that produce the technology have been investigated. Demand-pull and technology-push innovation models, which are among the innovation production models, have been validated. In addition, data from 1988-2017 of 11 high-income OECD countries are used to test theories. As predicted by the new growth theory, it is concluded that R&D investments and the number of patents led to a positive growth. It has been observed that technology-push and demand-pull innovation models are also compatible with the analysis results. Therefore, the interactive innovation model, which is a combination of both models and known as a more advanced model, has been proposed for innovation production. In addition, the cointegration relationship is determined in the data of the countries examined in the study. According to the causality test results, it is determined that there are mutual causality between the three data groups.