Identification and Estimation of Dynamic Stochastic General Equilibrium Models: Skewness Matters

本计画利用新的统计分布与计量经济学方法，探讨线性与非线性动态随机一般均衡（DSGE）模型中偏态对参数可辨识性与可估计性的影响。本计画的目的是分析DSGE模型，其中偏态不仅外生在误差项分布中，也内生在代理人的决策规则中。这将使人们能够估计不对称的生产创新、向下的工资刚性和较小但随时间变化的灾难概率的宏观经济影响，并仔细理清内生和外生偏斜的传导渠道和影响。由于偏度是经济风险的最重要的决定因素之一，其结果是显着的下一代DSGE模型，以缩小宏观经济和实证金融文献之间的差距。

This project investigates the effect of skewness on identifiability and estimability of parameters in linear and nonlinear dynamic stochastic general equilibrium (DSGE) models using new statistical distributions and econometric methods. The objective of this project is to analyze DSGE models in which skewness occurs not only exogenously in the error term distribution, but also endogenously in the decision rules of agents. This will enable one to estimate the macroeconomic implications of asymmetric production innovations, downward wage rigidities and a small but time-varying probability of disaster, and to carefully disentangle the transmission channels and effects of endogenous and exogenous skewness. Since skewness is one of the most important determinants of economic risk, the results are significant for the next generation of DSGE models in order to narrow the gap between the macroeconomic and empirical financial literature.