Detecting Multilevel Poverty-Causing Factors of Farmer Households in Fugong County: A Hierarchical Spatial–Temporal Regressive Model

Yuewen Jiang, Yanhui Wang, Wenping Qi, Benhe Cai, Chong Huang () and Chenxia Liang
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Yuewen Jiang: Key Laboratory of 3Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
Yanhui Wang: Key Laboratory of 3Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
Wenping Qi: China Centre for Resources Satellite Data and Application, Beijing 100094, China
Benhe Cai: Key Laboratory of 3Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
Chong Huang: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Chenxia Liang: State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China

Agriculture, 2022, vol. 12, issue 11, 1-21

Abstract: Accurate examination of poverty-causing factors and their mechanisms of poverty-stricken farmer households from a fine scale is conducive to policy implementation and long-term effective poverty reduction. The spatial effects in most previous studies are not fully considered, resulting in less reliability of detection results. Therefore, by fully considering background effects and spatial–temporal effects, this study designs a hierarchical spatial–temporal regressive model (HSTRM) to accurately identify the factors as well as mechanisms that cause poverty more reasonably. The empirical study of Fugong County, Yunnan Province, China, shows that: (1) There has been a certain degree of spatial effects in the study area over the years; therefore, spatial effects should be considered. (2) The poverty degree of farmer households in the study area is affected by individual factors and background factors. Therefore, poverty-causing factors should be observed at different levels. (3) Poverty-causing factors feature different action mechanisms. The influence of the village-level factors on poverty is greater than that of the household level. In addition, the village-level factors have a certain impact on the contribution of household-level factors to poverty. This study offers technical support and policy guidance for sustainable poverty reduction and development of poor farmer households.

Keywords: poverty-causing factors; spatial–temporal effects; poor households; HSTRM; action mechanisms (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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