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Forecasting Household Energy Consumption in European Union Countries: An Econometric Modelling Approach

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  • Katarzyna Chudy-Laskowska

    (Department of Quantitative Methods, The Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland)

  • Tomasz Pisula

    (Department of Quantitative Methods, The Faculty of Management, Rzeszow University of Technology, 35-959 Rzeszow, Poland)

Abstract

The article raises issues regarding the consumption of energy from both fossil and renewable sources in households. The research was carried out on the basis of data obtained from the Eurostat database, which covered the period from 1995 to 2021 and concerned the European Union countries. Increasing energy consumption and, thus, increasing household expenses affect their standard of living. The purpose of the analysis was to construct two econometric models for electricity consumption. The first model referred to the consumption of energy from fossil sources and the second from renewable sources. A forecast of energy consumption in households was also constructed on the basis of estimated models. Econometric modelling methods (multiple regression) and time-series forecasting methods (linear regression method, exponential smoothing models) were applied for the study. Research shows that the main factor that models energy consumption in households, both from fossil and renewable sources, is the final consumption expenditure of households (Euro per capita). The set of indicators for the models varies depending on the type of energy source. The forecast shows that the share of energy consumption obtained from fossil sources will decrease systematically, while the share of energy consumption from renewable sources will continue to increase systematically.

Suggested Citation

  • Katarzyna Chudy-Laskowska & Tomasz Pisula, 2023. "Forecasting Household Energy Consumption in European Union Countries: An Econometric Modelling Approach," Energies, MDPI, vol. 16(14), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5561-:d:1200376
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