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<p>Multidimensional poverty extends beyond income-based metrics, capturing the complex and interlinked deprivations experienced by coastal fisher households. This study introduces a multidimensional poverty assessment framework to evaluate the effectiveness of integrated interventions in model resilient fishing villages in coastal Bangladesh. Using cross-sectional data from 640 fisher households across model and control villages, the multidimensional poverty index (MPI) was calculated on nine key dimensions. Propensity score matching and nonparametric tests were employed to compare outcomes between the two groups. The results indicate a significant reduction in poverty among households in model villages, particularly in water supply and quality, education, gender equality, and asset ownership. MPI scores, headcount ratios, and poverty intensity were all markedly lower in the model villages. A binary logit regression model further identified household education, family size, livestock ownership, and on-farm income as key determinants of non-poverty. These results highlight the effectiveness of the model village approach and support the scale-up of integrated policies on infrastructure, education, and income diversification to enhance resilience and reduce multidimensional poverty in coastal fishing communities.</p>

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An empirical study on multidimensional poverty: evidence from model resilient fishing village in coastal Bangladesh

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • A. B. M. Mahfuzul Haque,
  • Sourav Mohan Saha,
  • Md Nahiduzzaman

摘要

Multidimensional poverty extends beyond income-based metrics, capturing the complex and interlinked deprivations experienced by coastal fisher households. This study introduces a multidimensional poverty assessment framework to evaluate the effectiveness of integrated interventions in model resilient fishing villages in coastal Bangladesh. Using cross-sectional data from 640 fisher households across model and control villages, the multidimensional poverty index (MPI) was calculated on nine key dimensions. Propensity score matching and nonparametric tests were employed to compare outcomes between the two groups. The results indicate a significant reduction in poverty among households in model villages, particularly in water supply and quality, education, gender equality, and asset ownership. MPI scores, headcount ratios, and poverty intensity were all markedly lower in the model villages. A binary logit regression model further identified household education, family size, livestock ownership, and on-farm income as key determinants of non-poverty. These results highlight the effectiveness of the model village approach and support the scale-up of integrated policies on infrastructure, education, and income diversification to enhance resilience and reduce multidimensional poverty in coastal fishing communities.