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| the Measuring of the Innovation Factors Input-Output Productivity |
| Wang Bihao1,Liang Rongcheng2 |
| (1.School of Economics and Management,East China Jiaotong University,Nanchang 330013，China；2.School of Labor and Human Resources of Renmin University of China, Beijing 100872,China) |
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Abstract The innovation factors allocation has much imperfect technology information during the input-output process, the input-output productivity (IOP) random changes prominently.Extracting the common factors from the input-output data set, consisting the predictor with the unobserved variables together, construct the factor augmented vertical auto-regression model (FAVAR).Analyzing the components of the stochastic change variance, can measure the IOP stochastic change degree accurately.The effect of the stochastic change includes the level effect, the scale effect and the sustained effect.The IOP stochastic change degree is indicated by its auto-regression perturbation, and divided into variances of the common factors and the predictor, and the co-variance of the unobserved variable and the IOP.It is to comparatively analyze the IOP stochastic change degree and its cause, based on the 669 quoted companies month, quarter, half year and whole year R&D data through the measuring thought, analyze the variables variances and change character with impulse responsible approach, then put forward the policy proposals.
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Received: 04 January 2021
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