Abstract

Given the strong link between economic growth and energy consumption, we construct a new set of energy consumption indices (ECI) to forecast GDP growth rates. The findings demonstrate the strong predictive power of the new indices. In particular, the electricity consumption index from the industrial sector has an excellent predictive performance and deserves the attention of the government and academia to help formulate economic growth targets. The mixed-frequency model with the Least Absolute Shrinkage and Selection Operator approach (MIDAS-LASSO) enables the full exploitation of energy consumption information for stable forecasting performance, even in the context of crisis fluctuations and geopolitical risk shocks. Furthermore, we apply forecast encompassing tests and variable selection to statistically investigate the predictive information. By analyzing energy consumption characteristics, we contribute to the economic growth hypothesis at the level of energy consuming sectors and provide new insights into GDP forecasting.

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