The Impact of Renewable Energy Sources on Economic Growth and CO2 Emissions - a SVAR approach

We analyze how an increasing share of Renewable Energy Sources on Electricity generation (RES-E) affects Gross Domestic Product (GDP) and Carbon Dioxide (CO2) emissions using a 3 variable Structural Vector Autoregressive (SVAR) methodology. We used a sample of four countries with different levels of economic development and social and economic structures but a common effort of investment in RES in the last decades. The period considered was 1960 to 2004. The existence of unit roots was tested to infer the stationarity of the variables. Through the impulse response functions (IRF), the SVAR estimation showed that, for all countries in the sample, except for the USA, the increasing RES-E share had economic costs in terms of GDP per capita. There was also an evident decrease of CO2 emissions per capita. The variance decomposition showed that a significant part of the forecast error variance of GDP per capita and a relatively smaller part of the forecast error variance of CO2 per capita were explained by the share of RES-E.