This paper investigates the role of the domestic value chain in transmitting the economic impact of Covid-19 lockdown measures. By employing techniques of complex networks analysis and input–output traditional tools, the study identifies those sectors that are key in the complex structure of the Italian supply chain and provides different rankings of the most ‘systemically important’ industries involved in the Covid-19 lockdown. The results suggest that by stopping the production process of many key sectors, the lockdown has led to a drop in input and output that, in turn, has generated a lock of about 52% of total circulating value added, 30% of which has been locked within indirect value chains. Further, by adding sectoral physical proximity indexes to the scenarios analysis, the method developed here provides a tool to guide governments in designing safe and efficient reopening policies.
The Italian value chain in the pandemic: the input–output impact of Covid-19 lockdown / Giammetti, Raffaele; Papi, Luca; Teobaldelli, Désirée; Ticchi, Davide. - In: ECONOMIA E POLITICA INDUSTRIALE. - ISSN 0391-2078. - 47:3(2020), pp. 483-497. [10.1007/s40812-020-00164-9]
The Italian value chain in the pandemic: the input–output impact of Covid-19 lockdown
Raffaele Giammetti
;Luca Papi;Davide Ticchi
2020-01-01
Abstract
This paper investigates the role of the domestic value chain in transmitting the economic impact of Covid-19 lockdown measures. By employing techniques of complex networks analysis and input–output traditional tools, the study identifies those sectors that are key in the complex structure of the Italian supply chain and provides different rankings of the most ‘systemically important’ industries involved in the Covid-19 lockdown. The results suggest that by stopping the production process of many key sectors, the lockdown has led to a drop in input and output that, in turn, has generated a lock of about 52% of total circulating value added, 30% of which has been locked within indirect value chains. Further, by adding sectoral physical proximity indexes to the scenarios analysis, the method developed here provides a tool to guide governments in designing safe and efficient reopening policies.File | Dimensione | Formato | |
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