Debt Burden of Farmers’ Households as Compared to Households of Other Careers
ภาระหนี้สินของครัวเรือนเกษตรทำนาเปรียบเทียบกับหนี้สินของครัวเรือนที่ประกอบอาชีพอื่น
by Areerat Lunlalad; อารีรัตน์ ลุนลลาด; Amornrat Apinunmahakul; อมรรัตน์ อภินันท์มหกุล
Title: | Debt Burden of Farmers’ Households as Compared to Households of Other Careers ภาระหนี้สินของครัวเรือนเกษตรทำนาเปรียบเทียบกับหนี้สินของครัวเรือนที่ประกอบอาชีพอื่น |
Advisor: | Amornrat Apinunmahakul
อมรรัตน์ อภินันท์มหกุล |
Issued date: | 12/8/2022 |
Publisher: | National Institute of Development Administration |
Abstract: |
This research aims to examine debt burdens of Thai households using the 2015 Socio-Economic Survey (SES) data conducted by the National Statistics Office (NSO). The study wants to find major factors that explain household debts especially those of farmer’ households, and to define some guidelines that might help to solve debt problems of farmer’s households. Four types of household debt are analyzed, i.e., (1) total household debts, (2) debts in doing agricultural business, (3) debts of household consumption, and (4) other debt burdens besides (2) and (3). The surveyed samples also divided into 4 groups, namely, (i) the whole sample of total households, (ii) rice farming households, (iii) other agricultural households, and (iv) non-agricultural households, respectively. Tobit regression model was used in this study to resolve the selection-bias problem. For the value of debt, in general, is always greater than or equal to zero indicating that there could be two groups of households with similar household’s characteristics but one with debt burdens, while another without. An Ordinary Least Square (OLS) regression could explain only the in-debt group but could not explain why another group is debt free. Therefore, Tobit regression would be more suitable for resolving the selection bias due to the lower bound of data on household debts. Independent variables used in the analysis were divided into 2 major categories consisting of the general characteristics of households and the economic status of households, respectively.
Major findings revealed that household’s debt burdens depend, firstly on whether there is any household member holding a bachelor’s degree or higher. For all types of debt particularly debts in running the agricultural business, it turns out that households with a bachelor graduate have a lower debt burdens than their counterpart with no bachelor member. It reflects that a higher education can offer other job opportunities outside the agricultural sector to household members. Consequently, household member with a higher education helps to reduce debts of farmers. Since all types of agriculture require a high operating cost. Agricultures also need to bear the risk of weather conditions that have a direct effect on the quantity of products and the amount of revenue. An increase in household income per capital significantly could decrease total liabilities and agricultural debt of households because higher income is a key to pay off debts. In addition, while the value of household total assets increased, all type of household debts increased also since value of assets could be used as collateral for loans. The higher the value of assets used as collateral; the higher the amount of loans households could borrow. On the contrary, the amount of annual remittance reflects household’s poverty, as this often occurred in rural households where parents sent money to their children and grandparents living in rural area. This type of family is called skipped generation family. Due to income insufficiency, people who struggled to make a living choose to migrate to work in urban area and send their income home. Therefore, the higher the remittance income, the higher the household’s debts. Consumption expenditure also is a major cause of household debts. Given other factors do not change (Ceteris paribus), when expense increase while income remains unchanged, there was a high possibility that household will need to ask for more loans for spending.
For an in-depth analysis on farmer’s household debts, given the data availability, agricultural lands used were classified into quintile groups in which household with the largest area of
lands for agriculture was used as the reference group. The study finds an interesting result that the more lands used for agriculture, the higher the household debts. For households with lots of agricultural lands and doing farming would have higher business expense, resulting in more agricultural debts than households with smaller agricultural lands. This reflected that agricultural debts grows in proportion with farmers’ agricultural lands. For running agricultural business, regardless of rice or non-rice farming, there would incur high operating costs ranging from purchasing seeds, fertilizer, wages for workers, including other expenditure for harvesting. Currently, there are many sources of loan for agriculture. Agriculturers could access the loans more easily and safely. Together with the fact that value of lands is a type of assets that can be used as a collateral for loans, households with the highest amount of agricultural lands thus will have the highest level of agricultural debt accordingly.
Based on all these findings, this study would like to suggest that government should promote higher education, especially to farmer’s households. Since households with a higher education graduate have lower agricultural debts. While running farming business bears a high operating costs and risks, promoting higher education for agricultural households with small amount of lands owned is considered as an important tool for providing them with job opportunity in other sector and a better quality of life in the future. Moreover, government should provide household with a principle knowledge on how to manage their debts by raising the awareness of household’s financial literacy that could help them to estimate their ability to pay off the debts and be more careful in incurring any debt burdens.
Once members of agricultural households are supported to have at least a bachelor education, they will have more choices for making a living. Higher education hence reduce risks in poor agricultural households with small amount of lands but have to adhere to their agriculture business with no other job opportunity. Furthermore, a higher education would help to bring various knowledge to future agriculture business in an efficient manner. |
Keyword(s): | ภาระหนี้สินครัวเรือน หนี้สินครัวเรือนเกษตร หนี้สินด้านการเกษตร |
Type: | Text |
Language: | tha |
URI: | https://repository.nida.ac.th/handle/662723737/5634 |
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