<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper proposes state space modeling and Kalman filtering as the theoretical foundation to explore the impact of China’s monetary policy on the offshore RMB market and capital flows. In the state space model, the relationship between observable and unobservable variables is established, with the Hidden Markov Model representing the state vector as a first-order Markov process to estimate unobservable variables. Additionally, a variable parameter state space model is proposed to alter the relationship between explanatory variables and the dependent variable. Kalman filtering, as the core of the state space model solution algorithm, calculates the likelihood function through prediction error decomposition to estimate unknown parameters. The optimal lag of the model is determined to be 2 after constructing the VAR model in the empirical analysis, and the first-order autoregressive model is used to calculate variable parameters. The elasticity coefficient of the depth of development of the offshore RMB market on capital flows is the most significant variable, with a value of 0.96. Following this, the RMB exchange rate has an elasticity coefficient of 0.78.</p>
</abstract>

This paper proposes state space modeling and Kalman filtering as the theoretical foundation to explore the impact of China’s monetary policy on the offshore RMB market and capital flows. In the state space model, the relationship between observable and unobservable variables is established, with the Hidden Markov Model representing the state vector as a first-order Markov process to estimate unobservable variables. Additionally, a variable parameter state space model is proposed to alter the relationship between explanatory variables and the dependent variable. Kalman filtering, as the core of the state space model solution algorithm, calculates the likelihood function through prediction error decomposition to estimate unknown parameters. The optimal lag of the model is determined to be 2 after constructing the VAR model in the empirical analysis, and the first-order autoregressive model is used to calculate variable parameters. The elasticity coefficient of the depth of development of the offshore RMB market on capital flows is the most significant variable, with a value of 0.96. Following this, the RMB exchange rate has an elasticity coefficient of 0.78.

The Interplay of Chinese Monetary Policy, the Offshore Renminbi Market, and Capital Flows: An Empirical Analysis via State Space Models

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper proposes state space modeling and Kalman filtering as the theoretical foundation to explore the impact of China’s monetary policy on the offshore...

The Interplay of Chinese Monetary Policy, the Offshore Renminbi Market, and Capital Flows: An Empirical Analysis via State Space Models

Published Online: Aug 05, 2024

Page range: -

Received: Mar 29, 2024

Accepted: Jun 19, 2024

DOI: https://doi.org/10.2478/amns-2024-1895

Keywords
State-space model, Kalman filter, Hidden Markov model, Likelihood function, Capital flows

© 2024 Weiran Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The Interplay of Chinese Monetary Policy, the Offshore Renminbi Market, and Capital Flows: An Empirical Analysis via State Space Models

Published Online: Aug 05, 2024

Page range: -

Received: Mar 29, 2024

Accepted: Jun 19, 2024

DOI: https://doi.org/10.2478/amns-2024-1895

KeywordsState-space model, Kalman filter, Hidden Markov model, Likelihood function, Capital flows

© 2024 Weiran Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
State-space model, Kalman filter, Hidden Markov model, Likelihood function, Capital flows