Euijune Kim (p), Seung-Woon Moon , Shigemi Kagawa

This paper identifies influences of national economic growth on emissions, trades and social costs of three nations of China, Japan and South Korea in Northeast Asian nations, developing a PM2.5-Multinational Computable General Equilibrium (PMCGE) model. The production of air pollutants are analyzed in terms of production-based emission by producers in supply process and consumption-based emission by consumers in demand process. The PMCGE model integrates a module of emission of PM2.5 and premature mortality with the economic equilibrium approach in a consolidated structure. The economy-wide effects on the emission could be quantified into changes in premature mortality and Value of a Statistical Life. The paper shows that Chinese economic growth by 1% could have the largest impacts of the GDP on the production and consumption based emissions by 0.996% and 1.002% respectively. The lowest one would be Japanese economy to achieve 0.771% of elasticity of the GDP with respect to production-based emission and 0.763% of that with respect to consumption-based emission. In addition, the industrial structure of Japan would be relatively effective to mitigate air pollution in three nations under the economic growth path: 1% of the GDP growth rate would result in negative change in the premature mortality and reduction in the emissions embodied in trade by 0.058% in spite of increasing the total trading volumes by 0.138%. This approach can provide public agents and stockholders with strategic insights into the efficiency, effectiveness and priority of the air pollution policies, contributing to establishing a cooperative framework with numerical targets of emission reductions and to developing a comprehensive policy package to address the various concerns and environmental costs shared by three nations.

Alexandre Lopes Gomes (p), Murilo Mazzotti Silvestrini

This paper analyses which countries need to reduce greenhouse gas (GHG) emissions as part of the overall goal of reducing emissions to the ideal level, as defined by the Intergovernmental Panel on Climate Change - IPCC, and which countries will suffer the largest reduction in gross production value (GPV). To identify these countries, the study uses the input-output (IO) and linear programming (LP) methodologies in multi-regional matrices, modelling scenarios of global GHG emission reduction to simulate different international agreements. The database comes from the WIOD headquarters for the year 2009. The results show the largest reduction in GHG and GPV in India and China. In a more ambitious scenario of reduction, the United States increases its responsibility and Russia becomes the country with the largest emissions reduction. The economic impact is largest in countries that have the most intense GHG emissions, and in the countries that make up the BRIC. This study allows us to explore the LP-IO methodology, demonstrating the importance of analysing the effect of international agreements and the use of cleaner productive structures.
Keywords: GHG Emissions; International Agreements; Multi-Regional Input-Output; Linear Programming.

Ferdaous Roussafi (p)

Energy transition tends to be at the heart of political and scientific agendas. Indeed, France has made national commitments such as National Strategy of Ecological Transition towards Sustainable Development and the energy transition law for green growth. This transition is also a matter of global concerns, as evidenced by some redefinitions of international (Kyoto Protocol) and European (EU Energy-Climate Package) energy policies. However, this transition is carried out according to different rhythms and temporalities according to the territories; it therefore seems essential, as many studies have pointed out, (Bridge et al., 2013; Hansen and Coenen, 2014; Murphy, 2015), to pay more attention to territorial dynamics in order to better understand the diversity of energy policy configurations and trajectories.

In this context, we seek to study the factors that determine the regional consumption of renewable energies in France. We build an econometric model that explains the evolution of the share of RE consumed at the regional level over the period 1990-2015. Our sample is made up of the 22 metropolitan regions and the French overseas departments. Using panel data methods allows us to study simultaneously the dynamics and heterogeneity of regions.

The results of the unit root tests allow us to maintain the assumption that the series are first-order integrated. The cointegration tests provide strong evidence that all panels in the data are cointegrated. Like Apergis et al., (2010), we employ a panel cointegration and error correction model to infer the causal relationship. The short-run estimates indicate that there are a statistically significant positive association between the share of renewable energy consumption and its lags and between this variable and economic growth measured by real GDP growth rate, but a statistically significant negative relationship between GDP per capita and renewable energy consumption and between this variable and nuclear energy production per capita. We also find that there is no environmental concerns effect explaining the growth of renewables in French regions.