Policy Shocks and Macroeconomic Fluctuations in a Two‐country Dynamic Stochastic General Equilibrium Model: Evidence from China*

• DOI: http://doi.org/10.1111/asej.12083
• Published date: 01 March 2016
• Date: 01 March 2016

Policy Shocks and Macroeconomic Fluctuations

in a Two-country Dynamic Stochastic General

Equilibrium Model: Evidence from China*

Yong Ma

Received 17 November 2013; accepted 22 November 2015

In this paper, we construct a two-country dynamic stochastic general equilibrium model

to investigate the sources of business cycles in China and the contributions of policy

shocks in economic fluctuations. The empirical results from Bayesian estimation show

that, apartfrom the traditional supply and demandshocks, monetary andfiscal policy

shocks also play important roles in determining China’s economic fluctuations. In

addition, we find significant feedbackeffects between monetary and fiscal policies in

China, indicating that policy coordination is an important feature of China’smonetary

and fiscal policies. Overall, these results not only shed new light on the policy factors

behind China’s economic fluctuations, but also provide new evidence that is helpful

for understanding the policy transmission mechanisms in China.

Keywords: Bayesian estimation, policy shocks, two-country dynamic stochastic

general equilibrium model.

JEL classification codes: E62, E63, H62.

doi: 10.1111/asej.12083

I. Introduction

China’s continued economic growth and rapid rise to becoming the second largest

economy in the world have spurred great interest in China’s economic g rowth and

development. Despite the wide variety of models intended to explainthe causes of

China’s economic success, few attempts have been made to explain economic

fluctuations in China. In the limited literature, there are two strands of models that

have addressed China’s business cycle and economic fluctuations: the business

cycle accounting (BCA) model and the dynamic stochastic general equilibrium

(DSGE) model.

The BCA method was first proposed by Mulligan (2002) and starts from a stan-

dard neoclassical growth model with time-varying wedges of efficiency, invest-

ment taxes, labor taxes and government consumption. Studies that have used

* Yong Ma (corresponding author): School of Finance, China Financial Policy Research Center,

Renmin University of China, No. 59 Zhong Guan Cun Street, Haidian District, Beijing 100872, China.

E-mail: mayong19828@hotmail.com. This research is supported by the National Natural Science

Foundation of China (Grant No. 71403277).

© 2016 East Asian Economic Association and John Wiley & Sons Australia, Ltd

Asian Economic Journal 2016, Vol.30 No. 1, 25–45 25

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this method to investigate China’s business cycles include Shi (2009); Christer

and Xu (2009) and He et al. (2009). Shi (2009) quantitatively investigates the size

and the relative importance of efficiency, labor, capital and foreign wedges in

China’s economic fluctuations over the period 2000–2007. His results show that

the capital wedge is the major driving force of the high investment rate after

2000, while the efficiency wedge has the largest impact on the fluctuations of

the GDP growth rate. Christer and Xu (2009) investigate the sources of business

cycle fluctuations in China and find that the efficiency wedge is the main source of

economic fluctuations, while the investment wedge and government consumption

wedge play minor roles in generating business cycles. In the framework of a

standard neoclassical open economy model with time-varying frictions, He

et al. (2009) study the relative contribution of the efficiency, labor, investment

and foreign debt wedges to business cycles and find that productivity best explains

the behavior of aggregate economic variables in China throughout the period of

1978–2006.

Because there is currently heated debate about the validity of the BCA method,

DSGE models have been gradually gaining popularity in recent years and an

increasing body of literature explores the sources of economic fluctuations in both

advanced and emerging economies (e.g. Smets and Wouters, 2003, 2007; Ireland,

2007; Lee, 2009; Justiniano et al., 2010; Choudhri and Malik, 2012). While such

micro-founded models have emerged as the basis of much current policy analysis,

the literature employing DSGE models is still relatively sparse for China. As an

example of recent work in a closed-economy DSGE model, Zhang (2009)

investigates whether money supply or interest rate rules are more effective in

managing the Chinese economy. Straub and Thimann (2010) develop an open-

economy DSGE model and analyze macroeconomic adjustment in China under

flexible and fixed exchange rate regimes. Mehrotra et al. (2011) construct a

small-scale DSGE model that features price rigidities, habit formation in

consumption and costs in capital adjustment, and evaluate the impact of a

rebalancing of the Chinese economy on its response to different shocks. Miao

and Peng (2011) study the sources of business cycles in China within the new

Keynesian DSGE model and find that credit shocks, productivity shocks and infla-

tion shocks are the major driving forces of economic fluctuations.

Overall, the existing DSGE studies on the Chinese economy are still in the early

stages and the features of China’s business cycle and economic fluctuations are

not well understood in the present literature. There is virtually no empirical

research that has used a two-country DSGE model to study the role of policy

shocks in China’s economic fluctuations and our paper intends to go some way

towards addressing this inadequacy. Our model is based on the classic DSGE

framework but modified with extensions that are crucial for the issues that our

paper intends to address. Following the recent literature (Ireland, 2007; Cogley

et al., 2010), we include external habit formation in consumption, partial dynamic

indexation in price setting, and a time-varying inflation target in the monetary

policy rule and a time-varying debt target in the fiscal policy rule. By introducing

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