Research Programs: Human Capital

Fundamental Research for Restoring Vitality and Improving Productivity in the Japanese Economy and Society

Project Leader/Sub-Leader


NISHIMURA Kazuo (Faculty Fellow)



The seriousness of Japan's long-term stagnation for more than a quarter of a century after the bubble economy is evident in various data. In the IMD (International Institute for Management Development) ranking of global competitiveness for 2020, Japan is ranked 34th, compared to Singapore (1st), Denmark (2nd), Switzerland (3rd), Hong Kong (5th), the United States (10th), Taiwan (11th), China (20th), South Korea (23rd), Malaysia (27th), and Thailand (29th). In terms of nominal GDP per capita in 2018, the U.S. ranks 5th, Singapore 8th, and Hong Kong (15th) is also higher than Japan's 23rd. South Korea is closing in on Japan at 27th place. This is mainly due to the fact that Japan has had low economic growth since 1990.


This research will conduct theoretical and empirical studies on human capital and economic productivity from the perspective of complex systems. We will conduct a nonlinear dynamic analysis of the macroeconomy, which explicitly includes human capital, and at the same time, we will analyze the behavior of different individuals at the micro level, and conduct questionnaires, brain measurements and analysis. The above research will take an interdisciplinary approach.

Just as the value of capital can be increased through investment, human knowledge and skills can be increased through educational investment. Recently, workers, including their abilities, are referred to as human capital. Human capital is an important variable that influences economic growth. Empirical studies of the contribution of human capital to productivity have concluded that productivity is determined not only by cognitive abilities such as reading, writing, and arithmetic, but also by non-cognitive abilities such as communication skills, and have emphasized investment in preschool education.

We have previously published empirical studies on human capital, comparing the effects of mathematics education, science education, and physics education, etc.

In 2014, we found that norms trained in early childhood are correlated with education and income (RIETI DP 14-J-011). This is consistent with the abovementioned finding that preschool education is most productive in developing non-cognitive abilities.

In 2017, we analyzed the relationship between changes in the learning status of science and mathematics subjects in high school and the number of patent applications and patent renewals after becoming an engineer by dividing the age group by the year when the curriculum guidelines were changed, and clarified whether the number of patent applications and patent renewals among engineers changed with the revision of the curriculum guidelines (RIETI DP 17-J-015).

In this study, we will pay particular attention to the following three points in addressing the problem. The first point is "the dynamic nature of an economy consisting of different economic agents," the second point is "theoretical and empirical analysis of human capital accumulation," and the third point is "analysis of cognition and decision making of different economic agents. As for the first point, we will conduct a dynamic analysis of the multi-sector growth model of a closed economy, and then analyze the dynamics of international linkages through trade among a large number of countries. Regarding the second point, the role of human capital in economic growth and business cycles will be theoretically analyzed in an economic dynamic model. Then, we will empirically analyze the role of education in human capital accumulation. As for the third point, we will measure brain activity and analyze how the cognition of economic agents affects learning and decision-making. Furthermore, the results of the above research will be applied to actual public-school education in order to realize actual improvement of human capital.

December 20, 2021 - May 31, 2024

(During the research project period, the research activity period is set from December 20, 2021 to November 30, 2023, and the data usage reporting period is set from December 1, 2023 to May 31, 2024.)