JACIII Vol.19 No.4 pp. 508-513
doi: 10.20965/jaciii.2015.p0508


Solving the Dynamic Stochastic General Equilibrium Model with Stochastic Volatility: An Application in China

Shangfeng Zhang*,**, Yuying Wang**, †, and Bing Xu**

*School of Economics, Zhejiang University
38 Zheda Road, Xihu District, Hangzhou, Zhejiang 310027, China

**Research Institute of Econometrics and Statistics, Zhejiang Gongshang University
18 Xuezheng Street, Xiasha Education Park, Hangzhou, Zhejiang 310018, China

Corresponding author

December 20, 2013
April 7, 2015
July 20, 2015
approximation, stochastic volatility, dynamic stochastic general equilibrium model

A first-order approximation technique is not suited to handle issues such as welfare comparison, time-varying variance. Following Schmitt-Grohe and Uribe [1], in this paper, we derive a second-order approximation to estimate the dynamic stochastic equilibrium model with stochastic volatility, to capture the different impacts of the level shocks and the volatility shocks. Furthermore, the paper presents an application of standard quantitative New Keynesian business cycle model, and the results shows the negative effects of stochastic volatility shocks. Furthermore, the paper presents an application of standard quantitative New Keynesian business cycle model, and the empirical results find that the level shocks have positive effects on consumption, investment and output, while the volatility shocks have negative effects on consumption, investment and output.

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Last updated on Aug. 18, 2017