Who Drives the Transition to a Renewable-Energy Economy? Multi-Actor Perspective on Social Innovation
Bongsuk Sung () and
Sang-Do Park ()
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Bongsuk Sung: Department of International Business Management, Woosong University, 171, Dongdaejeon-ro, Dong-gu, Daejeon 34606, Korea
Sang-Do Park: Department of International Business Management, Woosong University, 171, Dongdaejeon-ro, Dong-gu, Daejeon 34606, Korea
Sustainability, 2018, vol. 10, issue 2, 1-32
This study examines how various actors influence the transition to a renewable-energy economy. We employ a conceptual framework derived from a literature review and text-mining analysis and establish a panel data model for an empirical test using unbalanced panel data from 25 member countries of the Organization for Economic Co-operation and Development (OECD), for the period from 1990 to 2014. We establish a panel vector autoregressive (VAR) model in the first differences and use a bias-corrected least squares dummy variable (LSDVC) estimator to test complex dynamic relationships between government, the public, markets, the traditional energy sector (i.e., the sector that uses nuclear power, oil, coal and natural gas as sources for electricity) and the contribution of renewables to the total energy supply. We also perform Wald tests on the coefficients of variables estimated by LSDVC estimator to determine causal relationships between the variables. The results of this study reveal that government and markets directly promote the transition to renewable energy, whereas the traditional energy sector negatively and directly affects the transition. By contrast, the public does not directly influence the transition to a renewable-energy economy. This study also shows that the government and public have positive indirect effects on the transition, by interacting with the market. We also find convincing evidence of significant dynamic-path dependence in all estimations. Finally, we discuss some implications based on the findings of this study.
Keywords: transition to renewable-energy economy; big-data text-mining; LSDVC estimator for dynamic panel data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:10:y:2018:i:2:p:448-:d:130958
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