This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h ...This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model （GM （1, h））, always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method （abbreviated as FDGM （1, h））, is proposed accordingly. Then the feedback control equation and the parameters＇ solution of the FDGM （1, h） model are given. Finally, a real application is used to test the modelling accuracy of the FDGM （1, h） model. Results show that the FDGM （1, h） model is much better than the nonhomogeneous discrete grey forecasting model （NDGM） and the GM （1, h） model.展开更多
Human capital,as a synthesis of wisdom and physical fitness condensed in workers,is sometimes confused with technological innovation by existing literature.This paper makes comparisons between these two terminologies....Human capital,as a synthesis of wisdom and physical fitness condensed in workers,is sometimes confused with technological innovation by existing literature.This paper makes comparisons between these two terminologies.Technological innovation is a short-term activity that attaches importance to economic benefits while human capital accumulation is a long-term strategic process with lifelong benefits,and human capital is the foundation of technological innovation.In empirical part,this paper adopts Solow Residual Method to calculate stock,elasticity and growth rate of human capital of 10 countries after eliminating physical capital,labor force and technological innovation.It is found that human capital stock in the United States is the largest and human capital growth in China is the fastest.Calculation is followed by measurement.We construct a comprehensive index of human capital by using Index Weight Assignment Method and Two-level&Three-factor CES Function to measure and predict human capital level in China.Both calculating and measuring results show that growth rate of China’s human capital is around 5%.In the future,for high-quality economic development,China should give priority to human capital development and comprehensively improve human capital competitiveness.展开更多
基金supported by the National Natural Science Foundation of China(7117111370901041)
文摘This paper aims to study a novel expansion discrete grey forecasting model, which could aggregate input information more effectively. In general, existing multi-factor grey forecasting models, such as one order and h variables grey forecasting model （GM （1, h））, always aggregate the main system variable and independent variables in a linear form rather than a nonlinear form, while a nonlinear form could be used in more cases than the linear form. And the nonlinear form could aggregate collinear independent factors, which widely lie in many multi-factor forecasting problems. To overcome this problem, a new approach, named as the Solow residual method, is proposed to aggregate independent factors. And a new expansion model, feedback multi-factor discrete grey forecasting model based on the Solow residual method （abbreviated as FDGM （1, h））, is proposed accordingly. Then the feedback control equation and the parameters＇ solution of the FDGM （1, h） model are given. Finally, a real application is used to test the modelling accuracy of the FDGM （1, h） model. Results show that the FDGM （1, h） model is much better than the nonhomogeneous discrete grey forecasting model （NDGM） and the GM （1, h） model.
文摘Human capital,as a synthesis of wisdom and physical fitness condensed in workers,is sometimes confused with technological innovation by existing literature.This paper makes comparisons between these two terminologies.Technological innovation is a short-term activity that attaches importance to economic benefits while human capital accumulation is a long-term strategic process with lifelong benefits,and human capital is the foundation of technological innovation.In empirical part,this paper adopts Solow Residual Method to calculate stock,elasticity and growth rate of human capital of 10 countries after eliminating physical capital,labor force and technological innovation.It is found that human capital stock in the United States is the largest and human capital growth in China is the fastest.Calculation is followed by measurement.We construct a comprehensive index of human capital by using Index Weight Assignment Method and Two-level&Three-factor CES Function to measure and predict human capital level in China.Both calculating and measuring results show that growth rate of China’s human capital is around 5%.In the future,for high-quality economic development,China should give priority to human capital development and comprehensively improve human capital competitiveness.
