How indebted farmers perceive and address financial risk in environmentally degraded areas in Bangladesh

Environ Sci Pollut Res Int. 2020 Mar;27(7):7439-7452. doi: 10.1007/s11356-019-07374-2. Epub 2019 Dec 28.

Abstract

In Bangladesh, the recent uncontrolled growth of industries near farmland and unplanned urbanization made the agricultural sector the most vulnerable and a massive threat to the food security of the country. Agricultural farms near to industrial zones face high production costs (poor air-water-soil quality, high labor cost) and low-profit margin (poor crop yield and crop loss due to frequent natural hazards). The government policy in this matter is not proper due to a lack of information. As a consequence, many of these farm owners adopt agricultural credit by themselves to manage the production cost. Basically, credit itself creates some other financial risks and the farmers needed to adopt different measures to handle these financial risks. In-depth research on this matter is important to improve the situation by providing relevant information that policymakers can plan an efficient policy framework. However, previous literature has overlooked this area of research. In this study, the researcher collected data on 400 rice farmers (debtors) from six different districts in greater Dhaka division (most degraded area in Bangladesh) and adopted probit model to analyze the influential factors affecting farmers' financial risk management adoption decision and to identify the correlations between these decisions. The empirical findings indicate that education, access to technologies, household income, savings, and distance from the industrial areas are the major factors that affect farmer's adoption choice and most of the farmers are risk-averse. Moreover, the adoption choice of one risk management tool may motivate farmers to adopt another.

Keywords: Agricultural credit; Contract farming; Environment pollution; Marginal effect; Multinomial probit; Off-farm income diversification; Rice farming; Risk management.

MeSH terms

  • Agriculture* / statistics & numerical data
  • Bangladesh
  • Farmers*
  • Farms
  • Food Supply
  • Humans