A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various...A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that the monetary authority takes an aggressive stance to the current inflation pressure （there is a significant lagged response）, while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, overall our estimated model can successfully reproduce the stylized facts from actual data of Chinese business cycles and frequently can even outperform those forecasts from an unconstrained VAR.展开更多
将多主体协同创新理论与城镇化、工业化、信息化、农业现代化对创新体系发展推动作用的理论以及可持续发展理论相结合,构建区域创新体系DSGE(Dynamic Stochastic General Equilibrium,动态随机一般均衡)模型组、预期效用函数和拉格朗日...将多主体协同创新理论与城镇化、工业化、信息化、农业现代化对创新体系发展推动作用的理论以及可持续发展理论相结合,构建区域创新体系DSGE(Dynamic Stochastic General Equilibrium,动态随机一般均衡)模型组、预期效用函数和拉格朗日函数,进而形成了由30个模型组成的河南创新体系DSGE模型体系。以河南为例,运用贝叶斯方法和计量经济学方法等进行参数估计、模拟仿真和政策实验,从而分析出城镇化、工业化、信息化等的波动对河南创新体系状态变量和控制变量的作用效果。随后,利用H-P滤波法分析河南创新体系主要变量的波动特征,以验证模型的准确性,为推动区域创新体系发展提供政策依据。展开更多
文摘A small-scale, but highly-stylized dynamic stochastic general equilibrium model is estimated by the maximum likelihood method using Chinese quarterly data. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that the monetary authority takes an aggressive stance to the current inflation pressure （there is a significant lagged response）, while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, overall our estimated model can successfully reproduce the stylized facts from actual data of Chinese business cycles and frequently can even outperform those forecasts from an unconstrained VAR.
文摘将多主体协同创新理论与城镇化、工业化、信息化、农业现代化对创新体系发展推动作用的理论以及可持续发展理论相结合,构建区域创新体系DSGE(Dynamic Stochastic General Equilibrium,动态随机一般均衡)模型组、预期效用函数和拉格朗日函数,进而形成了由30个模型组成的河南创新体系DSGE模型体系。以河南为例,运用贝叶斯方法和计量经济学方法等进行参数估计、模拟仿真和政策实验,从而分析出城镇化、工业化、信息化等的波动对河南创新体系状态变量和控制变量的作用效果。随后,利用H-P滤波法分析河南创新体系主要变量的波动特征,以验证模型的准确性,为推动区域创新体系发展提供政策依据。
