Impact of human capital on endogenous power - evidence from agriculture-oriented town development projects across China

Abstract

With the continuous adoption of digital and information technologies in the agriculture sector, the level of modernization and digital transformation of agriculture is improving, which raises new requirements on education level, professional skills, and management experience of agricultural workers. There is now an inevitable trend of professionalization of agricultural production and farmers’ personal development, and a pressing need to comprehensively evaluate human capital beyond population and age distribution, extending to cover education, qualification, professional experience, and more.
Our research takes a strategic perspective to investigate issues encountered in agriculture-oriented town development projects and “rural revitalization” practice, incorporating human capital theory, scale economy theory, endogenous economic growth theory, and growth pole theory. We firstly develop a theoretical framework for the impact of human capital on the endogenous driving forces in agriculture-oriented town projects through a comprehensive literature review and secondary data. Screening data at the national level (including those projects approved by the Ministry of Housing and Urban-Rural Development and other authorities), 76 agriculture-oriented towns are selected for panel data collection and core variable measurements (from 2017 to 2022). A fixed effect model is employed to examine how the three dimensions of human capital (i.e., years of education, vocational training, work experience) affect the endogenous power.
Secondly, we empirically test the mediation effect of mechanism variables (such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization) between human capital and the endogenous driving forces of agricultural characteristic towns, and the moderator variables including technological innovation and application, and digitalization and digital transformation in agriculture.
Thirdly, we adopt a panel threshold effect model to further explore two specific dimensions of human capital, namely average years of education and vocational training.
Fourthly, gradual test method and Sobel method are applied to empirically test the mediation effect of mechanism variables such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization on the three dimensions of human capital and the endogenous driving forces, as well as the heterogeneity of this mediation effect across the three major regions of China (i.e., the eastern, the central, and the western).
Finally, we empirically test the moderating effects of technological innovation and application, and digitalization and digital transformation level on the relationship between the three dimensions of human capital and the endogenous driving forces of agriculture-oriented towns.
The main findings of this book are as follows:
(1) The three dimensions of human capital in agriculture-oriented towns are on the rise, yet there are differences across regions and supply chain functions. Firstly, overall, the average years of education for agricultural workers have increased, at a decreasing scale from Eastern, to Central, to Western China, while at increasing levels from agricultural planting, agricultural service, to agricultural product processing. Secondly, the degree of vocational training for agricultural workers is overall enhanced, with the eastern region generally higher than the central and western regions. Regarding their supply chain functions, processing-focused towns have the highest level of training, followed by service-focused towns. Thirdly, such heterogeneity is also observed in labor’s work experiences.
(2) We propose a comprehensive evaluation model with 13 indicators and the entropy method and principal component analysis method. The measured values show an overall increase over the six-year period. Regionally, the decline in the eastern, central, and western regions continued from 2017 to 2019; since 2020, it is high in the western and low in the central. The measured values of endogenous driving forces and the three dimensions of human capital present a linear relationship.
(3) Direct mechanism test. All three dimensions of human capital have a significant promoting effect on the endogenous driving forces of agriculture-oriented towns. Firstly, the average years of education has the most significant impact in central region, followed by the western and eastern regions. The impact coefficients decrease successively in western, central, and eastern regions they, and increase successively in agricultural product processing, service, and planting and breeding. Secondly, vocational training has a significant positive impact on endogenous driving forces in the western region, but not in other regions; it also has a significant positive impact on planting and breeding, but no significant impact in service and processing. Thirdly, work experience has a significant positive impact on endogenous driving forces in both central and western regions, but not in eastern region; it has the most significant impact on planting and breeding, then service, while agricultural product processing-focused towns do not pass the significant standard test.
The threshold effect test reveals: Firstly, there is a single threshold effect of the average years of education on the endogenous driving forces of agriculture-oriented towns in overall, central, and planting and service-focused town regions, and the positive driving effect of education level on endogenous driving forces shows a marginal decreasing trend as the average years of education of agricultural workers increase. Secondly, there is a single threshold effect of vocational training on the endogenous driving forces in overall, eastern, western, and planting and breeding agriculture-oriented towns. When the threshold value is exceeded, the impact of vocational training on endogenous driving forces shows a marginal increasing trend.
(4) Mechanism test. Mechanism variables such as agricultural industrial structure optimization, agricultural organization, and agricultural mechanization play a significant mediation role for the impact of human capital on the endogenous driving forces in agriculture-oriented towns, and exhibit heterogeneity across regions and business foci. Firstly, industrialization and digital transformation of the agriculture industry play a positive mediation role in the relationship between average years of education and vocational training and the growth of endogenous driving forces, while it has a significant masking effect on the relationship between work experience and the growth of endogenous driving forces. Secondly, scaling up of agriculture plays a partial mediation role in the mechanism of actions between average years of education, vocational training, and the endogenous driving forces; it plays a full mediation role in the mechanism of action between work experience and the endogenous driving force of agricultural characteristic towns. Thirdly, agricultural mechanization plays a partial mediation role in the mechanism of action between average years of education and vocational training of agricultural workers and the endogenous driving forces; it has a masking effect on the mechanism of action between work experience and the endogenous driving forces.
(5) Regression analysis. Technological innovation, and digitalization and digital transformation in the agriculture sector have significant moderation effects on the relationship between human capital and the internal driving forces of agriculture-oriented towns. They play different moderation roles in the relationship between average years of education, vocational training, and work experience and the internal driving forces of agricultural characteristic towns, and there are differences in the direction and significance of the moderating effects between regions and business foci.
(6) Based on the above analyses and findings, policy recommendations are made for coordinated development of agricultural human capital and the endogenous. Firstly, improve the quality of public services and attract high-quality talents to return to town and rural regions. Secondly, improve the education system, as the quality of secondary school education is the cornerstone for attracting high-quality talents to return to characteristic towns. Thirdly, improve the agricultural career development through vocational training, enhancing quality control and assessment, and enable tailored training approaches. Finally, establish an agricultural human capital development scheme, and allow capable individuals to make a difference.

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ORCID for Hao Dong: orcid.org/0000-0002-3458-4986

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