An Empirical Analysis Of The Impact Of China’s Vocational Education Funding On Manufacturing Development

With the continuous penetration of the third industrial revolution,various industrial countries have proposed new goals for industrial development.Under the world environment of "German Industry 4.0" and "Reindustrialization" in the United States,China promulgated the action plan of "Made in China 2025" in 2015.Vocational education is the main transportation channel of manufacturing labor,and vocational education funding is the material guarantee for vocational education to cultivate high-quality manufacturing labor.The State Council of China issued the National Vocational Education Reform Implementation Plan in 2019,which specifically emphasized that the status of vocational education should not be inferior to that of general education,and sounded the vanguard of vocational education reform in 2019.This reform specifically pointed out the focus of the reform-Improve the funding mechanism.Based on the conjecture that funding input is highly correlated with education,education and labor,labor and industrial economy,this article attempts to find out whether the investment in vocational education has a bearing on the development of the manufacturing industry(including the level of output value and structural conditions)within the geographic scope of China.Significantly affected? If there is a significant impact,what is the impact direction and magnitude? Furthermore,is there a threshold or range for the effect of occupational funding on the development of manufacturing? What is the performance of the above effects in the three major regions of China? How does the above role play in different levels of education in secondary and higher vocational education? These are also the research purposes of this article.I hope to answer the above questions and provide reference suggestions for China to steadily increase the scale of output value and optimize the structure of the manufacturing industry from the perspective of vocational education funding.On the basis of reading the relevant literature,this article clarifies the related concepts,and at the same time demonstrates through the literature the importance of education funding for education and the economy,the importance of talents for manufacturing,and the special importance of vocational education.Based on this logical relationship,this article describes the current situation of China ’s vocational education funding input and manufacturing development,and uses the panel data of each province in China from 2009 to 2016,using K-means clustering analysis method,from space and time.Perceptual recognition of the inter-provincial similarity between the investment of vocational education in various provinces in China and the development of manufacturing industry from two perspectives;the relative input efficiency of the investment in vocational education of various provinces in China to the development of manufacturing industry was calculated by data envelopment analysis.Finally,in the regression section of the empirical panel,it is divided into two parts: the impact on the output value and the structure.The fixed effect model is adopted according to the actual sample characteristics,and the Wald test and feasible generalized least squares(FGLS)are used to modify the heteroscedasticity to establish General panel regression model.Based on the general panel regression model,the threshold effect test is performed,and the threshold regression of the passed models is compared.On the basis of general panel regression and threshold regression,regional heterogeneity,education heterogeneity,and cross heterogeneity were further distinguished,and a robustness test was performed.The innovation of this article is mainly based on the study of China’s new policy of vocational education reform and the important role of manufacturing in the national economy,and from the new perspective of funding in the field of vocational education in China,to explore the specific impact on the development of manufacturing.At the same time,the general panel regression and threshold panel regression are used to not only obtain the direct influence direction,but also to explore whether the role of the core explanatory variable on the explained variable has a structural mutation and an optimal interval.This paper also discusses regional heterogeneity,education heterogeneity,and cross-regional and education heterogeneity,which is more in line with China’s national conditions and can provide specific recommendations for government education funding.The limitation of this paper is that the year interval for which data can be obtained is short.At the same time,only the amount of funds invested can be collected,and the lack of records of special purpose of funds,which makes the conclusion of this paper always stay at a more general level.In the above research,this article draws the following research conclusions.Unlike most other industries,the role of labor input is greater than that of fixed capital in increasing manufacturing output.The input of fixed capital can only increase the total volume of China’s manufacturing industry,but cannot effectively promote the structural upgrading of China’s manufacturing industry.On the contrary,China’s commitment to raise the level of urbanization is conducive to promoting the transformation of agricultural labor to urban industrial labor,and indirectly reducing the proportion of labor-intensive manufacturing,which is conducive to promoting the optimization and upgrading of China’s manufacturing structure.From a national perspective,the total investment in vocational education in various regions,especially the investment in secondary vocational education,is conducive to expanding the scale of manufacturing output value,reducing the proportion of laborintensive manufacturing,and increasing the proportion of capital-intensive manufacturing.Funding for higher vocational education has not yet shown a significant impact based on the entire country.In terms of the eastern,central,and western regions,the impact of total vocational education funding,vocational education funding,and higher vocational education funding on manufacturing varies.Most of the above effects have single or double threshold effects,so the direction of treatment needs to be combined with thresholds or threshold intervals,and policy recommendations for increasing or reducing corresponding inputs are made on a case-by-case and region-by-case basis.