Business Cycles in an Estimated DSGE Model of China

Biao Gu, Jianfeng Wang and Jingfei Wu

China Economic Journal, 2014, vol. 7, issue 3, 361-381

Abstract: A small-scale New-Keynesian dynamic stochastic general equilibrium model is estimated by maximum likelihood method using quarterly data of China. 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 both forward and backward components are important for the dynamics of output, inflation and real balances. The monetary authority will take a sufficient aggressive stance, with a significant lagged response, to the current inflation pressure, 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 shock and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, our estimated model overall can successfully reproduce the stylized facts of business cycles in the actual data of China and even frequently outperform those forecasts from an unconstrained VAR.

Date: 2014
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DOI: 10.1080/17538963.2014.947703

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