The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the tr...The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the trend of output values in the manufacturing industry.However,only a few statistical modellings have been established to investigate such associations.This study developed the correlation coefficient model and generalized linear model(GLM)to measure the single and interactive effects of the internal drivers on the changes of the output values.For the GLM,different predictive variables were developed to fit into the dataset,and the performance of the models were compared using fitness parameters.Furthermore,an industry survey dataset for 1,180 manufacturing enterprises in 2020 was used to validate the models.The use of the GLM combining land area,number of employees,scientific research input,and labor productivity may have a great potential to bolster capacity in monitoring and predicting the trend of output values in the manufacture industry.展开更多
This study incorporates value-added ratio （VAR） and productivity into the analytical framework of intra-product specialization （IPS） as a globally comparable index for international specialization status （ISS）, ...This study incorporates value-added ratio （VAR） and productivity into the analytical framework of intra-product specialization （IPS） as a globally comparable index for international specialization status （ISS）, to analyze the effect of domestic technological innovation, labor force investment, capital investment and foreign direct investment （FDI） spillovers on the ISS of developing countries. It also tests the effects empirically against the data from Chinese high-tech industries and enterprises. The results show that domestic technological innovation and the improved coordination of material capital and human capital are key internal drivers in the improvement of the ISS of Chinese high-tech industries, whereas FDI spillovers play a relatively limited role therein. Therefore, the key to China＇s industry upgrading is to tap and nurture the internal motive forces rather than to rely on FDI spillovers.展开更多
文摘The manufacturing industry is an important pillar of the national economy.It is of vital importance to develop statistical modellings in order to quantify the relationship between potential internal drivers and the trend of output values in the manufacturing industry.However,only a few statistical modellings have been established to investigate such associations.This study developed the correlation coefficient model and generalized linear model(GLM)to measure the single and interactive effects of the internal drivers on the changes of the output values.For the GLM,different predictive variables were developed to fit into the dataset,and the performance of the models were compared using fitness parameters.Furthermore,an industry survey dataset for 1,180 manufacturing enterprises in 2020 was used to validate the models.The use of the GLM combining land area,number of employees,scientific research input,and labor productivity may have a great potential to bolster capacity in monitoring and predicting the trend of output values in the manufacture industry.
基金funded by the Key Project of the National Social Science Fund of China(11AZD009)the Key Project of the Key Research Institute of University Humanities and Social Sciences,the Chinese Ministry of Education(2009JJD790044)+2 种基金the Project of the Zhejiang Key Research Base of the Social Sciences(11JDQY01YB)the General Program of the China Postdoctoral Science Foundation(2011M500979)the Fifth Group of Specially Funded Projects(2012T50533)
文摘This study incorporates value-added ratio （VAR） and productivity into the analytical framework of intra-product specialization （IPS） as a globally comparable index for international specialization status （ISS）, to analyze the effect of domestic technological innovation, labor force investment, capital investment and foreign direct investment （FDI） spillovers on the ISS of developing countries. It also tests the effects empirically against the data from Chinese high-tech industries and enterprises. The results show that domestic technological innovation and the improved coordination of material capital and human capital are key internal drivers in the improvement of the ISS of Chinese high-tech industries, whereas FDI spillovers play a relatively limited role therein. Therefore, the key to China＇s industry upgrading is to tap and nurture the internal motive forces rather than to rely on FDI spillovers.
