Spillover Effects and Temporal Dynamics on the Impact of Renewables on Labour Force: A World Perspective

Prompted by the need to reduce the concentration of CO2 in the atmosphere in order to limit global warming, several countries are adopting policies to incentivize the production of clean energy. In this context, a relevant aspect to be examined is the effect of expanding renewable resources on employment. Despite the large use of panel and time series analysis to investigate the topic, most of the econometric models generally consider a very small number of regressors. Furthermore, the spatial component, a potentially important determinant of employment, has been always neglected. By making use of a relatively large dataset of 59 countries spanning for 19 years (from 1996 to 2014), the present paper tries to fill these gaps by specifying a dynamic spatial panel data (SDPD) model with fixed effects and spatial error autocorrelation. The specification of both the individual and time fixed effects allows us to consider both spatial and temporal heterogeneity. Moreover, their presence and the long panel dimension avoid spurious correlations (Granger and Hyung, 1999). Proper marginal effects are then calculated also to reveal different impacts among countries worldwide. Our results confirm the positive role of expanding renewable energy production on employment, at the 5% significant level, leading also to significant total and direct short-term and long-terms marginal effects.