Projection of Post-Pandemic Italian Industrial Production through Vector AutoRegressive Models

Antonio Oliva, Francesco Gracceva, Daniele Lerede, Matteo Nicoli and Laura Savoldi
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Antonio Oliva: MAHTEP Group, Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Francesco Gracceva: Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Lungotevere Thaon di Revel, 76, 00196 Rome, Italy
Daniele Lerede: MAHTEP Group, Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Matteo Nicoli: MAHTEP Group, Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
Laura Savoldi: MAHTEP Group, Dipartimento Energia “Galileo Ferraris”, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

Energies, 2021, vol. 14, issue 17, 1-18

Abstract: Energy system models for the analysis of future scenarios are mainly driven by the set of energy service demands that define the broad outlines of socio-economic development throughout the model time horizon. Here, the long-term effects of the COVID-19 pandemic on the drivers of the industrial production in six energy-intensive subsectors are addressed using Vector AutoRegressive models. The model results are computed either considering or not considering the effects of the pandemic. The comparison to established pre-pandemic trends allows for validating the robustness of the selected model. The anticipated effect of the pandemic to 2040 shows a long-term reduction by 3% to 10%, according to the different subsector, in the industrial energy service demand. When the computed service demands are used as input to the TIMES-Italy model, which shows good capability to reproduce the energy consumption of the industrial sectors in the period 2006–2020, the impact of the pandemic on energy consumption forecasts can be assessed in a business-as-usual scenario. The results show how the long-term effects of the shock caused by the pandemic could lead, by 2040, to a total industrial energy consumption 5% lower than what was foreseen before the pandemic, while the energy mix remains almost unchanged.

Keywords: TIMES-Italy; Vector AutoRegressive model; industrial production projections; drivers for energy service demand; long-term effects of COVID-19 pandemic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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