Measure the Uncertainty of Technology Innovation Productivity According the FAVAR
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
Abstract：Extracting the common factors from the large data set,consisting the predictor with the unobserved variables together,the paper constructs the factor augmented vertical auto-regression (FAVAR)model.In order to analyze the components of the technology innovation productivity (TIP)uncertainty variance,the model can measure its uncertainty degree accurately.The results are as follows.①The shock of the uncertainty of the TIP has the level effect,the scale effect and the sustained effect.②The level effect has the line shock,and the others are the non-linear shock.③The TIP uncertainty degree can be expressed as the auto-regression stochastic volatility,the structural components are caused with the auto-regression perturbation terms,the common factors and the unobserved variables.The research significant is insisting on the productivity direction,decreasing stochastic factors shock during TIP uncertainty volatility through optimizing factors allocation and running coordination innovation,making it rising continually and steady.
王必好, 梁荣成. 基于FAVAR模型的技术创新效率不确定性测度[J]. 中国科技论坛, 2021(10): 40-49.
Wang Bihao, Liang Rongcheng. Measure the Uncertainty of Technology Innovation Productivity According the FAVAR. , 2021(10): 40-49.
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