3.9 Article

Farm income, inequality, and poverty among farm families of a flood-prone area in Bangladesh: climate change vulnerability assessment

Journal

GEOJOURNAL
Volume 86, Issue 6, Pages 2861-2885

Publisher

SPRINGER
DOI: 10.1007/s10708-020-10231-2

Keywords

Farm income; Inequality; Poverty; Climate change

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This study revealed significant farm income differences among districts in Mymensingh division, with agricultural income variation playing a crucial role in per capita income. Higher income from agriculture helped reduce income inequality within the districts. Remittance income showed higher income inequality, while agriculture was identified as the primary contributor to income disparity among farm households.
This paper examines the farm income differences, income inequality of farm households, parameters of income variability that ascertain vulnerability levels, and cost-income variability of agricultural crops in four districts of Mymensingh division in Bangladesh. Six hundred farm households from Mymensingh division were used as the source of data for the current study. The results of the analysis show that per capita income difference is significant in farm household among the districts, and agricultural income variation play an important role in per capita income. Higher income from agriculture contributed lower income inequality in the districts, even though employment income is dominant in most of the districts and highest income inequality is found in Netrokona district. Rice is the leading crop in most of districts, except Mymensingh where income share of other crops is high in the total agricultural income. Remittance income shows the higher income inequality among the districts that are lowest in employment and then agriculture. Agriculture is a primary contributor of inducing income disparity of farm households. In this context, we found that the key variation of agricultural income comes fromamanHYV andboroHYV rice crops. The cost and income of these rice crops was largely calculated based on the enhanced yields, higher irrigation, and chemical fertilizer and hired labor use per hectare land. By using the lognormal distribution under two scenarios (baseline, yield loss), we estimated the poverty rates resulted from the yield loss of rice production due to potential climate change impact in different districts. The unexpected yield loss of rice by climate change impact leads to the projection that poverty rates in Jamalpur and Netrokona districts would increase. It is, therefore, recommended that proper management of agricultural farms, crop diversification, and appropriate technology interventions are necessary to reduce income inequality and losses of farm income from climate change impact.

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