Quantifying the national innovation systems by US patents and their impact on economic growth

Abstract

This dissertation is an empirical analysis in finding the form of national innovation systems and their impact on economic growth. First, we examine how national innovation systems converge in 22 countries using five individual national innovation indices created using US patent data from 2010 to 2017. <br/> To do this, we analyze the localization, originality, concentration of assignees, diversification, and relative technological cycle time through patent citation analysis. Next, we can confirm that there is a developed NIS, catching-up NIS, middle-income NIS, and mixed NIS by clustering analysis. The developed NIS group includes Italy, UK, Germany, and France. The catching-up NIS group includes Korea, Taiwan, China, and Sweden. The middle-income NIS group includes Argentina, Brazill, Chile, Mexico, Malaysia, and Thailand. The mixed NIS group includes Norway, Denmark, Finland, Hong Kong, Singapore, and India. The above results show that the countries with catching-up NIS have higher economic growth rates, and then these five variables have proven to be very appropriate for the national innovation system for inter-country comparisons.<br/> Second, we review the impact of the five national innovation regimes on economic growth. Although there is a difference in statistical significance, the rate of economic growth increases as localization, dispersion of assignees, technological cycle time, diversification, and originality increase. Therefore, we use these five variables to generate a composite index of national innovation systems that can be compared across countries. In this process, we use Principal Component Analysis (PCA), Data Envelopment Analysis (DEA), the doubt of the benefit (BOD), and general weighting method. These results are compared to the Economic Complexity Index (ECI) developed by Houseman et al. (2011). <br/> According to this analysis, the results of the chronological method show that the index derived from the intuitively weighted method has an increasing trend as the income level goes up and time period passes. Through the panel analysis through the economic growth model, The highest value is observed in the model with the index by general weighting method<br/> Finally, we verify the technological turning point hypothesis presented by Lee (2013). According to him, Korea and Taiwan have specialized in technology with a short cycle time during the catching-up stage and have gradually increased their focus on technology with a long cycle time since passing the second technological turning point. On the other hand, he said that China had also passed a second technological turning point. we check the assertion. Empirical results show that increasing technological cycle time in Korea and Taiwan have a significant positive effect on economic growth, but in China, the decline in the technological cycle time shows a positive effect on economic growth.<br/> Summarizing the above three-part analysis, countries with a catching-up NIS show higher economic growth rates. However, countries that have remained at the middle-income level for the last 30 years failed to catch up with the income level of developed countries. Therefore, it is time for the middle-income countries to adopt a detour strategy that is better catch up by switching to a catching-up-type NIS specialized in a short cycle time of technologies such as Korea, Taiwan and China.<br/> However, countries such as Korea and Taiwan, which have experienced rapid growth as a catching-up-type NIS are under circumstances being caught up by China. Therefore, it is time for Korea and Taiwan to transit to a developed country-type NIS in order to overcome the catching-up of China and achieve sustained economic growth. In fact, the technological cycle time is increasing in Korea and Taiwan, which shows a significant positive effect on economic growth. However, China still has a short technological life cycle, and the gap between Korea and Taiwan is expected to decrease gradually.