Financial System Reforms and China's Monetary Policy Framework: A DSGE-Based Assessment of Initiatives and Proposals

Funke, Michael; Paetz, Michael

doi:10.2139/ssrn.2189458

“…Last but not least, we employ the framework developed by Chen et al (2012) and Funke and Paetz (2012) for modelling the wholesale branch of the commercial banking sector.…”

Section: Commercial Banks and Low-risk Firmsmentioning

confidence: 99%

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

Funke

¹

,

Mihaylovski

²

,

Zhu³

2015

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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.

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“…The lit-erature has not yet presented an all-encompassing DSGE model appropriate for modelling China's shadow banking sector, but several elements have been developed, and we naturally build on them. The papers byChen et al (2012) andFunke and Paetz (2012) develop a nonlinear DSGE model that captures China's nonstandard monetary policy toolkit. In this paper we augment that framework with a shadow banking sector, along the lines of Verona…”

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confidence: 99%

“…These features draw on elements of the DSGE models inGerali et al (2010),Chen et al (2012) andFunke and Paetz (2012) .…”

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confidence: 99%

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Exchange market pressure in OECD and emerging economies: Domestic vs. external factors and capital flows in the old and new normal

Aizenman

¹

,

Binici

²

2016

Journal of International Money and Finance

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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. Monetary policy transmission in China: A DSGE model with parallel shadow banking and interest rate control Against this background, our paper addresses the Chinese shadow bank issue and contributes to the literature on modelling parallel shadow banks and interest rate control in micro-founded dynamic stochastic general equilibrium (DSGE) frameworks. Few theoretical analyses exist to guide policymakers in this way. This paper is most closely related and complementary to three recent papers modelling a shadow banking sector, but differs in several respects. Verona et al. (2013) consider a financial accelerator DSGE model for the US economy with investment banks investing in less risky projects while formal retail banks provide funding to riskier firms. They are mainly concerned with the adverse effects of shadow banking for boom-bust events caused by a level of interest rates that is too low for too long. Meeks et al. (2014) are concerned about financial instability due to commercial banks unloading risky loans to off-balance sheet shadow banks via securization. Mazelis (2014) has investigated the impact of monetary policy shocks on aggregate loan supply in a DSGE framework with commercial banks and shadow banks. In contrast to Meeks et al. (2014), Mazelis (2014) does not assume that shadow banks are funded by the commercial banking sector; instead, shadow banks have to acquire deposits from the markets in order to function as intermediaries. The funding market is modelled via search and matching by shadow banks for available deposits of households. Our paper differs from the existing papers in a number of ways. None of the above papers focuses on the multifaceted interactions between nonstandard monetary policy, the traditional banking sector and the shadow banking sector in China. In our DSGE framework, in contrast, we analyze monetary policy transmission with parallel shadow banking and different degrees of interest rate control. This means, as a corollary, that we also investigate the impacts of financial liberalization and regulatory change in China on shadow banking. The remainder of the paper is organized as follows. Section 2 provides a brief overview of shadow banking activities in China: the products, the range of participants, and the reasons behind their rap...

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“…Under state control, the banks in China served the socialist plan of directing credits to specific projects dictated by political preference rather than commercial imperative. Traditionally, the PBOC 3 Among all existing DSGE modelling of Chinese economy, to our knowledge, only three have incorporated a banking sector: Chen et al ( 2012), Funke and Paetz (2012) and Xu and Chen (2009). T A B L E 1 The Chinese banking market 1997-2016 set loan quotas for each sector and mainly disbursed these through the branch network in each province.…”

Section: Dsge (Shadow) Banking and The Chinese Economymentioning

confidence: 99%