This paper explores the evaluation of energy-economic systems in the context of China, with a focus on shifting from traditional metrics like energy intensity and energy efficiency to a more comprehensive measure known as energy productivity. Energy productivity takes into account not only the relationship between energy consumption and economic output but also the broader economic benefits derived from energy usage. The study discusses both parametric methods, including the Solow residual method and Stochastic Frontier Analysis (SFA), and non-parametric techniques like Data Envelopment Analysis (DEA), which are commonly used to assess energy-economic systems. Each approach has its advantages and limitations, and their comparative effectiveness is examined. This analysis aims to provide insights into selecting appropriate evaluation methods for energy-economic systems, contributing to more informed and sustainable energy and economic policy decisions.