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Assessing interconnectedness and systemic importance of Chinese financial institutions.

ABSTRACT: This study proposes a directed acyclic graph (DAG)-based framework for generalized variance decomposition for investigating the heterogeneous return spillovers in financial system and measuring the systemic importance of financial institutions among 34 listed Chinese financial institutions from 2011 to 2023. Findings indicate pronounced information spillovers among institutions within the same sector due to contemporaneous causal relationships. Both static and dynamic financial network analyses highlight the significance of the securities sector. Dynamic structural characteristics align with macroeconomic development and are sensitive to internal and external shocks. Systemic importance assessment reveals that market size alone doesn't determine importance, with notable disparities between banking and non-banking sectors. State-owned and joint-stock commercial banks play a vital role in banking, while local government and private capital-controlled institutions are crucial in the securities sector. This research aids regulatory efforts in maintaining a balanced regulatory environment, ensuring market efficiency, and reducing operational costs.

SUBMITTER: Liu Z

PROVIDER: S-EPMC11295623 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Assessing interconnectedness and systemic importance of Chinese financial institutions.

Liu Zhe Z Wang Lihong L Huang Chong C Yang Benshuo B

iScience 20240708 8

This study proposes a directed acyclic graph (DAG)-based framework for generalized variance decomposition for investigating the heterogeneous return spillovers in financial system and measuring the systemic importance of financial institutions among 34 listed Chinese financial institutions from 2011 to 2023. Findings indicate pronounced information spillovers among institutions within the same sector due to contemporaneous causal relationships. Both static and dynamic financial network analyses ...[more]

PMID: 39100692

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Project description:Low-income communities have limited capital and access to money or loans from formal financial institutions. To solve the problems, the government provides solutions, one of them is by forming a microfinance program, namely Rural Agribusiness Business Development (PUAP). PUAP program is one of the grant activities to farmer group association (Gapoktan) with a total capital assistance of IDR 100 million. The problem with the 52,186 Gapoktan units that participated in PUAP activities, only 7,703 units (15%) were transformed into Agribusiness Microfinance Institutions (LKMA). This paper differs from others as it briefly explains the PUAP/MFI's institutional transformation and the factors that affect its sustainability, which is so far still limited discussed. The paper aims to see what transformations Gapoktan becomes an inclusive LKMA and the level of sustainability of the LKMA. The research was conducted in Kendal Regency, Central Java- Indonesia, in 2022 on 5 LKMA. The process of transforming LKMA into an inclusive financial institution is analyzed descriptively. LKMA sustainability levels were analyzed using a multidimensional scaling (MDS) approach with the Rapfish application. So far, MDS with the Rapfish application is still very limited for microfinance analysis. MDS analysis is employed because it is relatively simple and effective for looking at sensitive attributes in improving sustainability and generating leverage attributes that can be used for policy-making. The result study shows that the transformation of PUAP into LKMA is driven by the ability to improve legality, financial governance and diversify the customer's business field. The five LKMAs have a sustainability status of 'sufficient' in running their business, with an index value of more than 50%. The study recommends 1) the Indonesian government could assist LKMA in improving its legality and 2) LKMA's management should get training by experts to improve its financial capability to manage the cost saving.

Dataset Information

Assessing interconnectedness and systemic importance of Chinese financial institutions.

Publications

Assessing interconnectedness and systemic importance of Chinese financial institutions.

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