A new identification method of economic large shocks in the input–output framework: application to the COVID-19

Abstract

Abstract The COVID-19 pandemic has had a significant and unprecedented impact on the global economy, affecting both supply and demand in various industries. The literature on the pandemic has mainly focused on evaluating its real-time impact, using input–output analysis as a toolset. However, this paper aims to identify the magnitude of the large shock after observing its impacts on the economy. The proposed methodology adopts the main assumptions usually made in input–output analysis and focuses on the short term, assuming no significant changes in structures and prices. The approach is based on the technique of hypothetical extraction, which is generalized to consider the possibility of a shock simultaneously impacting all industries. Applying this approach to the Moroccan economy to identify the COVID-19 shock at the sectoral level, it appears that the most significant negative shocks were experienced by three industries, namely tourism, transport and mechanical industries, metallurgical, electrical. This is largely due to the nature of these industries, which are more sensitive to production constraints imposed to limit the spread of the pandemic. The results also show that other branches of activity have been severely impacted via the indirect channel of inputs rather than directly by the shock of the pandemic.

Keywords

• Large shocks
• Input–output analysis
• Partial hypothetical extraction
• Total hypothetical extraction
• Linkages
• COVID-19