Back to Search Start Over

A Case Study of Farmers’ Behavioral Motivation Mechanisms to Crack the Fractal Multidimensional Relative Poverty Trap in Shaanxi, China

Authors :
Yao Zhang
Jianjun Huai
Source :
Agriculture, Vol 13, Iss 11, p 2043 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

China’s approach to addressing rural poverty has evolved from a thorough resolution of absolute poverty to a focus on providing essential support for vulnerable individuals and improving the income and welfare conditions of those who are relatively poor, taking into account multiple dimensions. This study utilizes a dataset consisting of 526 research sets collected from the central region of Shaanxi Province. The research employs structural equation modeling to examine the fractal multidimensional relative poverty trap experienced by farm households. Additionally, the study investigates the behavior motivation mechanism that can potentially alleviate the multidimensional relative poverty trap at the farm household level. The study found that (1) farm households in the central Shaanxi region are caught in a multidimensional relative poverty trap, with education poverty and health poverty having a conduction and amplification effect; health poverty and education poverty amplify employment poverty; and consumption poverty amplifies education poverty and health poverty, and education poverty further amplifies information poverty. (2) Multidimensional relative poverty in farming households creates a self-reinforcing poverty trap, and community relative poverty amplifies the multidimensional poverty trap in farming households. (3) Farmers can overcome the multidimensional relative poverty trap through the behavior motivation mechanism.

Details

Language :
English
ISSN :
20770472
Volume :
13
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Agriculture
Publication Type :
Academic Journal
Accession number :
edsdoj.26a63ecc12df411d8d07d9888d318ce3
Document Type :
article
Full Text :
https://doi.org/10.3390/agriculture13112043