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The share of renewable energies has to increase significantly in the ongoing energy transition. Such a shift in production technology is expected to have noticeable effects on the energy sector's input structure that is required for its output. This study examines how changes in a country's energy mix affect its energy sector's input coefficients within an input–output framework, using Austria's renewable expansion act as a case study. Predicting input coefficients can be time-consuming and often relies on trends in past data. Our empirical approach is based on a fractional econometric model using panel data on the energy mix and input structures of energy sectors for 26 European countries, and can be efficiently and readily applied to the 26 countries covered in the model. We illustrate the prediction of input coefficients for Austria's energy sector in 2030. We find that input shares from the energy sector to itself would remain high, while mining inputs would decrease. Our model also predicts that increasing the share of renewable energy sources comes with a significant decrease in the share of labor inputs, mainly because operating renewable energy technologies requires less labor than operating non-renewable ones. The presented method allows to assess renewable energy policy plans to anticipate the effects of structural changes in national energy sectors. • A novel approach for modeling the energy sector's input coefficients is presented. • Input coefficients are explained by the energy mix in a fractional multinomial logit (FMNL) model. • The effects of Austria's renewable energy expansion act are analyzed in a case study. • An increase in renewable sources reduces the labor share and inputs from mining. • The approach is readily applicable for 26 European countries. [ABSTRACT FROM AUTHOR]