Greening monetary policy: evidence from the People’s Bank of China

2022 ◽  
pp. 1-12
Author(s):  
Camille Macaire ◽  
Alain Naef
Keyword(s):  
Monetary Policy ◽  
Bank Of China

Greening Monetary Policy: Evidence from the People's Bank of China

2021 ◽  
Author(s):  
Banque de France RPS Submitter ◽  
Camille Macaire ◽  
Alain Naef
Keyword(s):  
Monetary Policy ◽  
Bank Of China

scholarly journals Influence of the People’s Bank of China Monetary Policy on the Country’s Economic Development

2019 ◽  
Vol 35 (2) ◽  
pp. 223-250
Author(s):  
Svetlana V. Bekareva ◽  
◽  
Ekaterina N. Meltenisova ◽  
Ekaterina A. Shikhovtsova ◽  
Yuying Song ◽  
...  
Keyword(s):  
Monetary Policy ◽  
Economic Development ◽  
Bank Of China

Effect of monetary policy on bank risk: does market structure matter?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muntazir Hussain ◽  
Usman Bashir ◽  
Ahmad Raza Bilal
Keyword(s):  
Monetary Policy ◽  
Market Structure ◽  
Risk Taking ◽  
Bank Risk ◽  
Monetary Policy Transmission ◽  
Content Type ◽  
Bank Of China ◽  
Policy Transmission ◽  
Chinese Banking Industry

PurposeThe purpose of this paper is to investigate the risk-taking channel of monetary policy transmission in the Chinese banking industry. This study also investigates the role of various other factors in the risk-taking channel.Design/methodology/approachThis study used panel data from 2000 to 2012, and a dynamic panel model (Difference GMM) was applied.FindingsThe empirical findings of this paper suggest that loose monetary policy rates increase bank risk-taking. Unlike previous studies, the results of this paper suggest that the bank-specific factors (size, liquidity and capitalization) do not significantly affect the risk-taking channel. However, the market structure does have a stabilizing effect on monetary policy transmission and the risk-taking channel. Higher market power weakens the risk-taking channel of monetary policy transmission.Practical implicationsOf significance to the policymakers' point of view is that loose monetary policy induces banks to take excessive risks. However, such effects can be mitigated by encouraging a proper level of market power in banking markets.Originality/valueThis study investigated the risk-taking channel of monetary policy transmission for the Chinese banking industry. Due to the unique features of the People's Bank of China (PBC, Central Bank of China) policy, this study also contributes to the literature by comparing price-based and quantity-based monetary policy tools and their effectiveness in financial stability and monetary policy transmission. Furthermore, the role of market structure is also investigated in the risk-taking channel.

scholarly journals Research on Forecasting of China's Monetary Policy Based on Random Forest Algorithm.pdf

2020 ◽  
Author(s):  
chuanxin qiu
Keyword(s):  
Neural Network ◽  
Monetary Policy ◽  
Random Forest ◽  
Prediction Accuracy ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Random Forest Algorithm ◽  
Bank Of China ◽  
Macroeconomic Indicators ◽  
Neural Network Algorithm

This paper uses the random forest algorithm model to quantify and predict the monetary policy of the People's Bank of China under the input of 16 indicators macroeconomic indicators. It is compared with three other machine learning algorithms (CART decision tree, support vector machine and neural network algorithm), discrete selection model and combined prediction model. The results show that the random forest algorithm shows better prediction accuracy in predicting the direction of the central bank's monetary policy.

scholarly journals Research on Forecasting of China's Monetary Policy Based on Random Forest Algorithm.pdf

2020 ◽  
Author(s):  
chuanxin qiu
Keyword(s):  
Neural Network ◽  
Monetary Policy ◽  
Random Forest ◽  
Prediction Accuracy ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Random Forest Algorithm ◽  
Bank Of China ◽  
Macroeconomic Indicators ◽  
Neural Network Algorithm

This paper uses the random forest algorithm model to quantify and predict the monetary policy of the People's Bank of China under the input of 16 indicators macroeconomic indicators. It is compared with three other machine learning algorithms (CART decision tree, support vector machine and neural network algorithm), discrete selection model and combined prediction model. The results show that the random forest algorithm shows better prediction accuracy in predicting the direction of the central bank's monetary policy.

The evolution of China's monetary policy: on the horns of a dilemma

2021 ◽  
Vol 9 (1) ◽  
pp. 83-108
Author(s):  
Ramaa Vasudevan ◽  
Keyword(s):  
Monetary Policy ◽  
Financial Sector ◽  
The State ◽  
Bank Of China ◽  
International Lending ◽  
The Us ◽  
International Role

This paper explores the evolution of monetary policy at the People's Bank of China (PBoC) in the context of the distinct path China has adopted in fostering the international role of the renminbi. The paper highlights the challenges faced by the PBoC as it seeks to promote the use of the renminbi in international lending in particular, while simultaneously seeking to contain and discipline the inherent instability and potentially disruptive logic of finance. The problem it faces is not simply that of negotiating the impossible trinity, but rather the dilemma posed by its attempt to step out of the shadow of the US and forge an independent global role for the renminbi, while asserting control over the contours of its developing financial sector. The Chinese experiment tests the limits of the capacity of the state to tame finance.

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