Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)

Research on the Determinants of Peasants’Land Mortgage in China

Authors
Ji Luo, Ying Wang, Fan He
Corresponding Author
Ji Luo
Available Online April 2018.
DOI
10.2991/cmsa-18.2018.61How to use a DOI?
Keywords
land property rights; type of peasants; mortgage willingness; bivariate probit model
Abstract

Based on the survey data of Peasants in China, the bivariate Probit model is constructed to analyze the factors affecting Peasants’ land mortgage Determinants. The results show that the willingness of Peasants' land mortgage is higher, and the education level, the rationality of loan term and the understanding degree of the relevant policies have significant positive impacts on the needs of the mortgage. Moreover, the impact of cultivated land area, social insurance, family annual income and interest rate on the financing needs of different types of Peasants is different.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
April 2018
ISBN
10.2991/cmsa-18.2018.61
ISSN
1951-6851
DOI
10.2991/cmsa-18.2018.61How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ji Luo
AU  - Ying Wang
AU  - Fan He
PY  - 2018/04
DA  - 2018/04
TI  - Research on the Determinants of Peasants’Land Mortgage in China
BT  - Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
PB  - Atlantis Press
SP  - 270
EP  - 274
SN  - 1951-6851
UR  - https://doi.org/10.2991/cmsa-18.2018.61
DO  - 10.2991/cmsa-18.2018.61
ID  - Luo2018/04
ER  -