Analysis of Monetary and Multidimensional Poverty Drivers Among Agricultural Households in Togo Using a Weighted Logit Framework

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Abstract

Assessments of poverty among agricultural households in Sub-Saharan Africa often rely on either monetary or multidimensional indicators considered separately, overlooking key structural constraints. This study investigates the determinants of both monetary and multidimensional poverty among agricultural households in Togo. Using nationally representative EHCVM 2021/22 data from 2893 households, monetary poverty is measured using the Foster–Greer–Thorbecke Index, while multidimensional poverty is assessed with the Alkire–Foster method. A survey-weighted logit model is employed to identify the drivers associated with each poverty dimension. Results show that multidimensional poverty (59.40%) is more widespread than monetary poverty (51.50%). Education substantially reduces poverty risk, whereas larger household size, limited market access, and residence in the Savannah region increase it. Economic and natural shocks are negatively associated with monetary and absolute poverty, while cooperative membership raises the likelihood of being poor. Investment in livestock (TLU) reduces monetary poverty but increases multidimensional deprivation. These findings highlight that poverty among agricultural households in Togo is shaped by interconnected socioeconomic and institutional constraints rather than income deprivation alone. Therefore, integrated strategies aligned with the Sustainable Development Goals, particularly those promoting education, rural credit access, market integration, and resilience-building, are essential for achieving effective and context-specific poverty reduction.

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Miawonene, S. D., Bi, J., Adabe, K. E., Zhu, H., Wang, J., Ndossi, J., & Agbokou, K. S. (2026). Analysis of Monetary and Multidimensional Poverty Drivers Among Agricultural Households in Togo Using a Weighted Logit Framework. Sustainability (Switzerland), 18(1). https://doi.org/10.3390/su18010336

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