Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)

The Reform and Optimal Allocation of Rural Financial Institutions from the Perspective of Multi-Task Principal-Agent Theory

Authors
Wang Jianfeng, Chen Wei, Aiying Mu
Corresponding Author
Wang Jianfeng
Available Online 1 May 2020.
DOI
https://doi.org/10.2991/assehr.k.200428.094How to use a DOI?
Keywords
the reform of the rural financial institutions, the best ratio of the agricultural policy-oriented financial institutions, multi-task principal-agent model
Abstract
This paper study the reform and the best allocation of the rural financial institutions with a multi-task principal-agent model. Our analysis shows that: (1) When the ability of the peasant to participate in the financial activities is weak, the radical commercialization reform of financial institutions will lead to lower social welfare. Otherwise the agricultural policy-oriented financial institutions will promote the rural financial market. (2) The original ability of the peasant to participate in the financial activities has an inverse relation to the best ratio of the agricultural policy-oriented financial institutions in the market. (3) If the government has another ways to improve the ability of the peasant to participate in the financial activities with lower cost, setting the agricultural policy-oriented financial institutions is not a good way to improve the rural financial market.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Cite this article

TY  - CONF
AU  - Wang Jianfeng
AU  - Chen Wei
AU  - Aiying Mu
PY  - 2020
DA  - 2020/05/01
TI  - The Reform and Optimal Allocation of Rural Financial Institutions from the Perspective of Multi-Task Principal-Agent Theory
BT  - Proceedings of the 6th International Conference on Humanities and Social Science Research (ICHSSR 2020)
PB  - Atlantis Press
SP  - 439
EP  - 445
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200428.094
DO  - https://doi.org/10.2991/assehr.k.200428.094
ID  - Jianfeng2020
ER  -