COVID-19 and a trade-off between health and economics: an extended inoperability model for Italy

Abstract

PurposeThe recent COVID-19 has obliged governments to enact large-scale policies to contain it. A topic of economic debate is the quantification of the impact that these policies can create in the economy, with the aim of activating regulatory mechanisms to minimize this impact. In this vein, this study aims to propose a quantification of the effects of the Italian government policy that blocks nonessential production activities.Design/methodology/approachThe authors use a multisectoral extended inoperability model on the social accounting matrix of Italy. The analysis identifies the pandemic’s impact on outputs, endogenous demands, value-added and disposable incomes of institutional sectors.FindingsThe construction and real estate sectors revealed a significant contraction followed by the retail trade and hotel and catering services sectors. The output contraction further impacts the value-added generation, disposable income and final demand components.Originality/valueThe current pandemic is alleged to have a greater impact than the epidemics of the past century, considering the present dimension of the world economy and the increasing interconnections between industries and institutions. In this scenario, it is challenging to safeguard not only human health and life but also the economy. Hence, there is a need to establish a trade-off between health and economics; and in this regard, the current study empirically quantifies the impact of health measures on the economy. The findings of this study help identify the sectors that are more prone to disaster effects and also present the structure of income circular flow in the Italian economy.

Investigating COVID-19 spillovers in the US economy with a dynamic CGE model

“…It serves as a data framework of general economic equilibrium that makes it the most suitable instrument for simulations and impact analyses, because it captures all the transmissions and feedback impulses in different stages of production, distribution, accumulation and use of income (Socci et al. , 2021, 2023). The analytical structure of a SAM is the basis for modelling purposes, in particular for both fixed-price multiplier models, and calibration of CGE (Pyatt, 1988).…”

“…The coercive selective blockade of non-essential production activities (Bonadio et al ., 2020; Elenev et al ., 2020), the voluntary sectoral blockade of production activities unable to comply with health regulations and the voluntary blockade on the final demand side of deferred consumption require the adoption of a general and disaggregated approach in a mainly short-term context (Socci et al. , 2021, 2023).…”

“…Quantifying the economic impact of the pandemic cannot therefore ignore the precision and accuracy that must be reserved for the construction and inclusion of the control variable of the economic model used. The coercive selective blockade of non-essential production activities (Bonadio et al, 2020;Elenev et al, 2020), the voluntary sectoral blockade of production activities unable to comply with health regulations and the voluntary blockade on the final demand side of deferred consumption require the adoption of a general and disaggregated approach in a mainly short-term context (Socci et al, 2021(Socci et al, , 2023.…”

“…Materials and methods 3.1 The social accounting matrix (SAM) According to Pyatt and Round (1985) and Reinert and Roland-Holst (1997), a SAM is an accounting scheme that represents the complex links of an economic system by capturing the transactions among all economic agents. It serves as a data framework of general economic equilibrium that makes it the most suitable instrument for simulations and impact analyses, because it captures all the transmissions and feedback impulses in different stages of production, distribution, accumulation and use of income (Socci et al, 2021(Socci et al, , 2023. The analytical structure of a SAM is the basis for modelling purposes, in particular for both fixedprice multiplier models, and calibration of CGE (Pyatt, 1988).…”