An Empirical Analysis of the Impact of Population and Economy Factors on Regional Energy Consumption

Energy is a pivotal concern for the sustainable growth of the economy and society. Our study centers on a region along the southeastern coast of China, where we investigate the population, economic status, and energy usage to develop a predictive model for energy consumption that is informed by demographic and economic factors. Initially, we crafted a two-level index system that captures the region's population, economic, and energy consumption dynamics, and we have confirmed its validity through correlation analysis. In light of the region's social context, we chose logarithmic and linear functions, as well as a seasonal ARIMA model, to interpret the temporal trends in population, GDP, and energy consumption. Finally, we employed Ridge regression and Lasso regression methods to construct the energy consumption prediction models, with the outcomes being thoroughly analyzed. The projections from these models serve as a robust basis for policy recommendations that are intended to promote sustainable energy and economic development.