• Energy Research
• engineering and technology close

Abstract The mothballing option has been studied in the literature, but mainly in decision theoretic frameworks. This paper looks at it from a strategic point of view and applies it to an incumbent-entrant framework. In particular, based on the recent strategic interactions between OPEC and the shale oil industry, we conduct a case study where the incumbent OPEC is a flexible producer that competes with a representative shale oil firm. Upon entry, the latter produces a fixed amount but it can apply the mothballing option in times of low demand. Our main results are threefold. First, we find that under low demand uncertainty, the mothballing option has a negative effect on the value of the entrant. Second, a large market share of the entrant will stimulate mothballing, caused by a so-called squeeze strategy of the incumbent. Third, we show that a higher demand elasticity induces mothballing as confirmed in our empirical analysis of the (shale) oil market.

In this paper, we deal with the issue of measuring the Agenda 2030 at the urban level in Italy; the results are useful for the policy analysis and dissemination of sustainable development at the local level. The proposed tool merges 53 available economic, social and environmental elementary indicators into 16 composite indices and one composite dimension representing 16 out of 17 Sustainable Developments Goals (SDGs) adopted by the United Nations in 2015. The contribution of the paper is twofold: While the results of the indices show the geographical and demographic heterogeneity within the country when considering each of the 16 dimensions, the methodological discussion highlights the complexity of the phenomena, due to the multidimensional definition of the Agenda 2030.

Many predictions and conclusions in the climate change literature have been made and drawn on the basis of theoretical analyses and quantitative models that assume exogenous technological change. One is naturally led to wonder whether those conclusions and policy prescriptions hold in the more realistic case of endogenously evolving technologies. In previous work we took a popular integrated assessment model and modified it so as to allow for an explicit role of the stock of knowledge which accumulates through R&D investment. In our formulation knowledge affects both the output production technology and the emission-output ratio. In this paper we make further progress in our efforts aimed to model the process of technological change. In keeping with recent theories of endogenous growth, we specify two ways in which knowledge accumulates: via a deliberate, optimally selected R&D decision or via experience, giving rise to Learning by Doing. As an illustration, we simulate the model under the two versions of endogenous technical change and look at the dynamics of a selected number of relevant variables, including growth rates of GDP and physical capital, as well as total emissions and rate of domestic abatement.

The aim of this paper is to estimate the potential impacts of different COVID-19 scenarios on the Italian energy sector through 2030, with a specific focus on transport and industry. The analysis takes a multi-disciplinary approach to properly consider the complex interactions of sectors across Italy. This approach includes the assessment of economic conditions using macroeconomic and input-output models, modelling the evolution of the energy system using an energy and transport model, and forecasting the reaction of travel demand and modal choice using econometric models and expert interviews. Results show that the effect of COVID-19 pandemic may lead to mid-term effects on energy consumption. The medium scenario, which assumes a stop of the emergency by the end of 2021, shows that energy-related emissions remain 10% lower than the baseline in the industry sector and 6% lower in the transport sector by 2030, when compared with a pre-COVID trend. Policy recommendations to support a green recovery are discussed in light of the results.