Forecasting Energy Consumption in the EU Residential Sector

Area of Science:

• Econometrics
• Energy Economics
• Environmental Science

Background:

• Accurate forecasting of residential energy demand is crucial for energy policy and infrastructure planning.
• Understanding the drivers of energy consumption, such as economic growth and climate, is essential for reliable predictions.

Purpose of the Study:

• To introduce and validate a top-down econometric methodology for forecasting residential energy demand.
• To apply the methodology to four European countries: Germany, Italy, Spain, and Lithuania.
• To analyze the relationship between energy demand, GDP per capita, and weather conditions.

Main Methods:

• Development of a logarithmic dynamic linear constant model for energy consumption.
• Estimation of demand as a function of heating degree days and gross domestic product per capita.
• Application of econometric techniques to analyze country-specific elasticities and forecast future demand.

Main Results:

• The proposed methodology is suitable for Germany, Italy, and Spain, but not Lithuania.
• Elasticity of demand with respect to GDP per capita is negative for Germany (-0.629) and positive for Italy (0.837) and Spain (0.249).
• Germany and Italy show higher sensitivity to weather conditions, with an 8% and 9% demand increase expected during cold periods, respectively.

Conclusions:

• The econometric model effectively forecasts residential energy demand in selected European countries.
• Economic growth and climatic factors significantly influence residential energy consumption patterns.
• Country-specific economic and climatic conditions necessitate tailored approaches to energy demand forecasting.