Vulnerability to poverty of rural farm households in Thailand
Keywords:Vulnerability to poverty, poverty, risk management, feasible generalized least square, farm household
This research intends to estimate vulnerability to poverty, specify vulnerable groups and identify strategies that households use to address the exposure to risk of rural farm households in Northeastern and Northern Thailand. This study was conducted in four provinces of Thailand in the Northeastern region (Kalasin and Buri Ram provinces) and the Northern region (Chiangmai and Nan provinces). Data on a total of 1,400 households was collected in the year 2014. The research methodology applied was the feasible generalized least square (FGLS) method, which was employed to determine how log consumption impacts the welfare status of households. The result on vulnerability to poverty analysis was reached by the feasible generalized least square (FGLS) method. Upon subjecting the data to analysis, the first stage of the OLS revealed that 48% of the variation in log consumption (a measure of well-being) can be explained by the following factors: household size square, family member education, household head education, non-farm occupation of the household head, disabled persons, unemployed family members, non-farm full-time employees, own livestock, monetary assets, tangible asset value, total borrowing, expenditure on risks, risk severity, unemployment, theft of producer goods, crop loss via insects, working disability by accident to the household head, and theft of crops.
The estimates show that about 53.57% of households were vulnerable to poverty. The comparison of observed poverty status based on the vulnerability index shows that 75% of farm households are poor, whereas another 25% are non-poor. The classification of poverty status based on observed poverty status and the vulnerability index can be classified into four groups. Firstly, poor households with high vulnerability to poverty account for 9.64%. Secondly, households that are currently not poor but have a high vulnerability to being poor in the future account for 43.93%. Thirdly, poor households that have a low vulnerability to poverty account for 19.14%. Finally, non-poor with low vulnerability to poverty account for 27.29%. Policy recommendations for the factors influencing poverty are as follows: 1) theft of agricultural commodities; farmers should install lighting, keep watch at night, use technology networks like video cameras or smart phones to catch thieves; 2) a solution to the disabled family member problem is suggested by the government creating social worker jobs, education in specific skills and employment education and planning for a smart city for the disabled; 3) for crop loss caused by insect and plant disease issues it is suggested that farmers reduce pesticide use, employ crop rotation and practice organic farming; 4) unemployment problems can be solved by increasing the specific skills of labor consistent with factory demand and government consideration of a migrant policy; 5) providing rural education by using innovative tools and methods to the challenges posed by home-school distance; beyond formal education, the study suggests education in specific skills and employable education.
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Firstly, I would like to give special thanks to The Thailand Research Fund (TRF) for supporting this work under grant RSA5680050. Secondly, I would like to express my deepest gratitude to my previous institution, the Faculty of Economics, Khon Kaen University, for their supporting of grant as well. Thirdly, I thank the Faculty of Economics at Sriracha, Kasetsart University at Sriracha Campus, for its supporting grant as well. Fourthly, I would like to thank the people in our research group with whom we had long conversations regarding the subject of this research. Finally, my thanks to our collaborators who provided the data used in this research.
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