Estimating Rural Premium and Financial Crisis Effect on the Nexuses between Food, Energy, and Water Consumption on Urban-Rural Income Gap in South–Eastern Asian Countries Using Pooled Regression Analysis

Authors

  • Khambai Khamjalas School of Economics and Trade, Hunan University, Yuelu District, Changsha 410006, P.R. China

DOI:

https://doi.org/10.54536/ajase.v3i1.2600

Keywords:

Energy, Food, Income Inequality, Poverty Gap, Poverty Rates, Water

Abstract

Poverty and inequality reduction and access to affordable clean energy and clean water are among the global sustainable development goals. Yet, researchers have overlooked how food, energy, and water (FEW) resources can be instrumental in reducing the urban-rural income gap. In this article, ordinary least squares regression analysis was used to estimate rural premium and financial crisis effect on the nexuses between food, energy, and water consumption on urban-rural income gap using a sample of data pooled from three Asian countries: China, India, and Indonesia over 2000 to 2019. No significant urban or crisis effect on the poverty rate was established. However, a significant crisis effect on the poverty gap was established, but not on the urban premium. A significant positive interaction between food insecurity and water was established. Water supply improves agricultural production, improves food security, and reduces poverty by raising income. However, modern clean energy is associated with rising income inequality. Modern energy technologies benefit a few wealthier individuals investing in the energy and agriculture sectors. Therefore, improved water access, particularly to support food production and affordability, and efficient utilization of clean fuels and technologies among all individuals, regardless of socio-economic class, are crucial to escaping poverty and achieving prosperity.

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Published

2024-04-06

How to Cite

Khamjalas, K. (2024). Estimating Rural Premium and Financial Crisis Effect on the Nexuses between Food, Energy, and Water Consumption on Urban-Rural Income Gap in South–Eastern Asian Countries Using Pooled Regression Analysis. American Journal of Applied Statistics and Economics, 3(1), 80–91. https://doi.org/10.54536/ajase.v3i1.2600