Applied Stochastic Models in Business and Industry

Semiparametric spatio‐temporal analysis of regional GDP growth with respect to renewable energy consumption levels

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Abstract This article evaluates the impact of renewable energy consumption levels on GDP growth. Renewable energy sources may be significantly more costly as compared to classical (fossil) sources. Hence, high relative proportion of renewable energy has the potential of obstructing economic growth. On the other hand, in developed countries, renewable energy adoption processes are often subject to prominent state‐level incentives, administrative ingerence, and fiscal subsidies. For stratified and unbiased evaluation of the overall effect of renewables on GDP, this article applies a spatio‐temporal analysis of GDP growth at the regional NUTS2 level in a conveniently selected group of 11 spatially adjacent yet heterogeneous EU member states. As macroeconomic covariates are controlled for, along with spatial and temporal interdependencies, there is no sign of negative impact of renewable energy consumption on GDP growth. While the estimated overall effect is positive and statistically significant, its economic significance is small. Yet, given the data and economies considered, we may conclude that renewable energy consumption does not exert negative influence on economic growth rates.

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Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.