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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.

PurposeThis work aims at designing an indicator for detecting and forecasting price volatility and speculative bubbles in three markets dealing with agricultural and soft commodities, i.e. Intercontinental Exchange Futures market Europe, (IFEU), Intercontinental Exchange Futures market United States (IFUS) and Chicago Board of Trade (CBOT). This indicator, designed as a demand/supply odds ratio, intends to overcome the subjectivity limits embedded in sentiment indexes as the Bull and Bears ratio by the Bank of America Merrill Lynch.Design/methodology/approachData evidence allows for the parameter estimation of a Jacobi diffusion process that models the demand share and leads the forecast of speculative bubbles and realised volatility. Validation of outcomes is obtained through the dynamic regression with autoregressive integrated moving average (ARIMA) error. Results are discussed in comparison with those from the traditional generalized autoregressive conditional heteroskedasticity (GARCH) models. The database is retrieved from Thomson Reuters DataStream (nearby futures daily frequency).FindingsThe empirical analysis shows that the indicator succeeds in capturing the trend of the observed volatility in the future at medium and long-time horizons. A comparison of simulations results with those obtained with the traditional GARCH models, usually adopted in forecasting the volatility trend, confirms that the indicator is able to replicate the trend also providing turning points, i.e. additional information completely neglected by the GARCH analysis.Originality/valueThe authors' commodity demand as discrete-time process is capable of replicating the observed trend in a continuous-time framework, as well as turning points. This process is suited for estimating behavioural parameters of the agents, i.e. long-term mean, speed of mean reversion and herding behaviour. These parameters are used in the forecast of speculative bubbles and realised volatility.

The ongoing economic stagnation and low inflation rates affecting EU have refuelled the debate on the role and the limits of monetary policy in pushing the economic growth. Given the tight margins for fiscal policy for EU state members, traditional and unconventional monetary policies are becoming more looked-for to break out of this condition. However, the main issue on whether the real or nominal aspects prevails still remains. In this situation, a framework able to identify and analyse any interaction between economic and financial flows becomes crucial to detect the dynamics pushing towards expansions or contractions resulting from monetary policies. Therefore, the aim of this paper is to investigate the direct and indirect impact of monetary policies implemented by the European Central Bank on the main Italian macroeconomic variables both in aggregate and disaggregate terms. For this purpose we use Dynamic Computable General Equilibrium model calibrated on the financial Social Accounting Matrix for Italian economy.

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