Socio-Economic Dynamics of Energy: A Micro-Level Regression Approach to Domestic Consumption in India

Abstract

This study highlights the importance of forecasting micro-level energy consumption for effective energy planning and Clean Development Mechanism (CDM) initiatives. Traditional time series models face challenges due to numerous influencing factors. To address this, a stepwise regression model is introduced for predicting household energy consumption using micro-level survey data from Kerala, India. This model enhances forecast accuracy by incorporating household-specific data, offering a granular approach to energy consumption analysis. The findings reveal that socio-economic, demographic, geographic, and family attributes significantly impact household energy demand. These factors shape consumption patterns, emphasizing the complexity of household energy needs. The study identifies a strong variation in energy consumption across different expenditure classes, highlighting disparities in energy demand among various income groups. Per capita income is found to be the most influential variable affecting household energy consumption. Higher-income groups show a strong relationship between energy demand, per capita land area, and residential space. In contrast, lower-income groups are more influenced by variables such as average age and literacy levels. These insights emphasize the role of socio-economic conditions in determining household energy requirements. This research provides valuable implications for energy policymakers, offering a model that enhances forecasting accuracy. By recognizing the key determinants of household energy consumption, policymakers can design targeted interventions to promote sustainable energy use. The study underscores the necessity of incorporating socio-economic diversity in energy planning, ensuring that strategies align with the distinct needs of different income groups, thereby fostering effective energy management and sustainability.