This paper studies the impact of renewables on nuclear energy consumption in 15 OECD countries over the period 1991–2015. We find that the share of renewables (in total electricity production) has negative long-run effects on both nuclear energy consumption per capita and the share of nuclear energy (in total electricity production) while controlling for real GDP per capita, the proportion of carbon emissions from electricity production, and energy dependency. By taking proper account of both cross-section dependence and heterogeneity in the error-correction models, we find that a one percentage point increase in the share of renewables is associated with a 1.8% decrease in nuclear energy consumption per capita and a 2.7% decrease in the share of nuclear energy. Two main implications emerge. First, our results indicate a suppressive effect of renewables on nuclear energy in electric power generation, raising the possibility of restraining installed nuclear capacity through sustained penetration of renewables in OECD countries. Second, our results suggest the limited ability to replace nuclear energy with renewables in electric power generation. As a consequence, raising the share of renewables by rapidly deploying renewable energy technologies on a massive scale may not lead to the intended outcome of greatly reducing the dependence on nuclear energy in OECD countries.
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The first author acknowledges financial support from the Japanese MEXT [Monbu Kagakusho] Grant-in-Aid for Scientific Research (C) [Project/Area Number 17K03581].
Apergis N, Payne JE, Menyah K, Wolde-Rufael Y (2010) On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth. Ecol Econ 69:2255–2260CrossRefGoogle Scholar
Baek J, Pride D (2014) On the income–nuclear energy–CO2 emissions nexus revisited. Energy Econ 43:6–10CrossRefGoogle Scholar
Baltagi BH, Moscone F (2010) Health care expenditure and income in the OECD reconsidered: evidence from panel data. Econ Modelling 27:804–811CrossRefGoogle Scholar
Breitung J (2000) The local power of some unit root tests for panel data. In: Baltagi B (ed) Nonstationary panels, panel cointegration, and dynamic panels, Advances in econometrics, vol 15. JAI, Amsterdam, pp 161–178CrossRefGoogle Scholar
Chudik A, Pesaran MH (2015) Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressions. J Econometr 188:393–420CrossRefGoogle Scholar
de Cavalcanti VTV, Mohaddes K, Raissi M (2011) Growth, development and natural resources: new evidence using a heterogeneous panel analysis. Q Rev Econ Finance 51:305–318CrossRefGoogle Scholar
de Cavalcanti VTV, Mohaddes K, Raissi M (2015) Commodity price volatility and the sources of growth. J Appl Econometr 30:857–873CrossRefGoogle Scholar
Ikegami M, Wang Z (2016) The long-run causal relationship between electricity consumption and real GDP: evidence from Japan and Germany. J Policy Modeling 38:767–784CrossRefGoogle Scholar
Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econometr 115:53–74CrossRefGoogle Scholar
Jaforullah M, King A (2015) Does the use of renewable energy sources mitigate CO2 emissions? a reassessment of the US evidence. Energy Econ 49:711–717CrossRefGoogle Scholar
OECD Nuclear Energy Agency (2017) Impacts of the Fukushima Daiichi accident on nuclear development policies. (No. 7212). OECD, ParisGoogle Scholar
Pesaran MH (2004) General diagnostic tests for cross section dependence in panels. (No. w1229). CESifo, MunichGoogle Scholar
Pesaran MH (2006) Estimation and inference in large heterogenous panels with multifactor error structure. Econometrica 74:967–1012CrossRefGoogle Scholar
Pesaran MH (2007) A simple panel unit root test in the presence of cross section dependence. J Appl Econometr 22:265–312CrossRefGoogle Scholar
Pesaran MH (2015) Testing weak cross-sectional dependence in large panels. Econometr Rev 34:1089–1117CrossRefGoogle Scholar
Pesaran MH, Smith R (1995) Estimating long-run relationships from dynamic heterogeneous panels. J Econometr 68:79–113CrossRefGoogle Scholar
Pesaran MH, Smith R, Im KS (1996) Dynamic linear models for heterogeneous panels. In: Matyas L, Sevestre P (eds) The economics of panel data: a handbook of theory with applications, 2nd rev edn. Kluwer Academic, Dordrecht, pp 145–195CrossRefGoogle Scholar
Pesaran MH, Shin Y, Smith R (1999) Pooled mean group estimation of dynamic heterogeneous panels. J Amer Stat Assoc 94:621–634CrossRefGoogle Scholar
Sadorsky P (2009) Renewable energy consumption, CO2 emissions, and oil prices in the G7 countries. Energy Econ 31:456–462CrossRefGoogle Scholar
York R, McGee JA (2017) Does renewable energy development decouple economic growth from CO2 Emissions? Socius 3:1–6Google Scholar