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Spatial diversity of Village Funds in reducing Poverty in West Sumatra Province

Guswandi Guswandi  -  Krisnadwipayana University, Indonesia
*Siska Amelia  -  Krisnadwipayana University, Indonesia

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Abstract
One of the efforts to improve the community's welfare and poverty alleviation requires an integrated development program and synergized based on local resources. One of the efforts is the village fund program, are funds provided for villages sourced from the state budget and are used for government administration, implementation of development and empowerment of village communities. This paper examines the spatial diversity of the effectiveness of the Village Fund in reducing poverty in West Sumatra Province from 2015 to 2020 (data from the Ministry of Finance). The unit of research analysis is the regency/municipal that receives the Village Fund assistance. This study uses Geographically Weighted Regression, with dimensions of observing the allocation of Village Funds and poor people. The study results show that the Village Fund cannot reduce poverty in the beneficiary regencies/municipals. The number of Village Funds disbursed increases every year, but the number of poor people also increases; only three districts, namely Limapuluh Kota, Pesisir Selatan, and Kepulauan Mentawai, have decreased in 2020. The Village Fund Program is ineffective in reducing poverty in West Sumatra Province due to the Village Fund allocation percentage being more prominent for village government operations. The allocation of Village Funds for the administration of village government is much larger than what is mandated by law, which is 30%. The main objective of the Village Fund Program is to eradicate poverty and reduce inequality. To achieve this noble goal, it is necessary to evaluate the distribution of Village Funds. This study looks at the effectiveness of the Village Fund in reducing poverty, and looks at the spatial diversity of the effectiveness of the Village Fund in beneficiary regencies/municipals.
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Keywords: Regional Development, Poverty, Geographically Weighted Regression

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