Monetary Policy Transmission in China: A DSGE Model with Parallel Shadow Banking and Interest Rate Control

Abstract

The paper sheds light on the interplay between monetary policy, the commercial banking sector and the shadow banking sector in mainland China by means of a nonlinear stochastic general equilibrium (DSGE) model with occasionally binding constraints. In particular, we analyze the impacts of interest rate liberalization on monetary policy transmission as well as the dynamics of the parallel shadow banking sector. Comparison of various interest rate liberalization scenarios reveals that monetary policy results in increased feed-through to the lending and investment under complete liberalization. Furthermore, tighter regulation of interest rates in the commercial banking sector in China leads to an increase in loans provided by the shadow banking sector.

Shadow Banking, Bank Liquidity and Monetary Policy Shocks in Emerging Countries: A Panel VAR Approach

“…However, the decline is short lived. The finding is first of all contrary to other studies such as Nelson et al (2018) and Funke et al (2015) whose findings suggest an increase in shadow banking in the event of a positive shock in the policy rate. However, our results are in support of the risk-taking proposition, which suggest that increasing the policy rate increases risk and in turn make market participants to reduce their appetite for risky assets.…”

Rebalancing in China: A taxation approach

“…ζ S > ζ d because there are tighter credit constraints for private firms than for SOEs (Boyreau-Debray, 2003;Boyreau-Debray and Wei, 2005;Dollar and Wei, 2007;Poncet et al, 2010;Song et al, 2011). To bypass these credit constraints some private firms use FDI (Héricourt and Poncet, 2009;Ju and Wei, 2010;Poncet et al, 2010) or shadow banking (Tsai, 2002;Krugman, 2011;Li, 2014;Funke et al, 2015). These are not modeled here to maintain a simple framework.…”

“…Regarding nominal rigidities, we set the price rigidity parameter η at 0.55 in China for the benchmark calibration; this value goes up to 0.65 during certain reforms (which is close to Bénassy-Quéré et al, 2013, where η = 0.67 in China). As for preferences, the elasticity of substitution across domestic goods is set at 7 (close to the calibration of Funke et al, 2015, and as in Rotemberg and Woodford, 1997, and Bénassy-Quéré et al, 2013, the elasticity of substitution between domestic and foreign goods is fixed at 1.5 (as in Backus et al, 1994, andAuray et al, 2011), and the share of imports in China's consumption is equal to 0.2 (Bénassy-Quéré et al, 2013). The households' intertemporal elasticity of substitution is equal to that of Funke et al (2015), that is, 1.…”

“…As for preferences, the elasticity of substitution across domestic goods is set at 7 (close to the calibration of Funke et al, 2015, and as in Rotemberg and Woodford, 1997, and Bénassy-Quéré et al, 2013, the elasticity of substitution between domestic and foreign goods is fixed at 1.5 (as in Backus et al, 1994, andAuray et al, 2011), and the share of imports in China's consumption is equal to 0.2 (Bénassy-Quéré et al, 2013). The households' intertemporal elasticity of substitution is equal to that of Funke et al (2015), that is, 1. Concerning firms, the capital share α d and the depreciation rate of capital δ d are fixed at 0.6 (to reach the highest investment rate possible in the model) and 0.14 (close to Funke et al, 2015), respectively.…”

“…The households' intertemporal elasticity of substitution is equal to that of Funke et al (2015), that is, 1. Concerning firms, the capital share α d and the depreciation rate of capital δ d are fixed at 0.6 (to reach the highest investment rate possible in the model) and 0.14 (close to Funke et al, 2015), respectively. The initial level of technology remains equal to 53% of the most developed countries level (Source: St Louis Fed Stats and author's calculations), and credit constraints are more relaxed than those in Coeurdacier et al (2015).…”