This presentation is based on a research project conducted by Mariam Tsulukidze and Yana Hovhannisyan (International School of Economic- ISET). This empirical model examines the relationship between CO2 and renewable energy (RE) consumption for countries from different groups: advanced, developed and developing economies (classified by GDP per capita) for the period 2005-2013.

1. The impact of
renewable energy
on CO2 emissions
International School of Economics (ISET)
Yana Hovhannisyan, Ana Kinkladze, Mariam
Tsulukidze
19.06.2017 1

2. 1.General Idea 2.Related Literature 3.Methodology
4. Conclusion
5. Recommendations
Agenda
2
6. Q&A session

3. Why to be concerned?
• Climate change
• Air pollution
• Millions of deaths
• Huge environmental footprint
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4. 960grams of CO2
VS
1-34 grams of CO2
Renewable energy – A
Solution
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5. • Energy –related carbon
dioxide emissions have
been decreasing
• This is not related to an
economic downturn
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International Energy Agency

6. 1. This research project addresses this
issue and aims to investigate the links
between the exploitation of renewable
energy sources and CO2 emissions per
capita
Research Question (RQ)
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2. Environmental Kuznets Curve
Hypothesis

7. • Iceland – The Leader with 77.4 %
• Norway and Sweden are preparing
for phase-out
• Kuwait 0% of renewable energy
consumption
• Forestation rate does plays a role
• Car usage a great contributor to CO2
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8. • Arouri et al. (2012)
Energy Consumption, Economic Growth and
CO2 Emissions in Middle East and North
African Countries.
• Apergis and Jebli (2015)
Does Renewable Energy Consumption and
Health Expenditure Decrease Carbon Dioxide
Emissions?
• Silva et al. (2012)
The impact of Renewable Energy Sources on
Economic Growth and CO2 Emissions - a
SVAR approach.
Literature Review
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9. • Sulaiman (2013)
• The potential of Renewable Energy.
• Chiu and Change(2009)
• What proportion of renewable energy
supplies is needed to initially mitigate CO2
emissions in OECD member countries?
Literature Review
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10. •60 countries were chosen, 20 in each group
Advanced, Developed, Developing
• 2005-2013 time period was observed
The main data sources
• The World Bank
• “Organisation Internationale des Constructeurs
d’Automobiles”(OICA)
Methodology and Applied model
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11. 𝐿𝑛(𝐶𝑂2𝑖𝑡)
= 𝛽0 + 𝛽1𝑖 𝑅𝐸𝐶𝑖𝑡 + 𝛽2𝑖 𝐺𝐷𝑃𝑖𝑡 + 𝛽3𝑖 𝐹𝑜𝑟𝑒𝑠𝑡𝑖𝑡
+ 𝛽4𝑖 𝐶𝑎𝑟𝑖𝑡 + 𝛿1 𝐴𝑑𝑣𝑖 + 𝛿2 𝐷𝑒𝑣𝑖 + 𝛼𝑖 + 𝐸𝑖𝑡
• 𝐶𝑂2𝑖𝑡 − CO2 emissions metric tons per capita
• 𝑅𝐸𝐶𝑖𝑡 − Renewable energy consumption per capita
• 𝐺𝐷𝑃𝑖𝑡 − Gross Domestic Product per capita
• 𝐹𝑜𝑟𝑒𝑠𝑡𝑖𝑡 − The percentage of the land area
• 𝐶𝑎𝑟𝑖𝑡 − Cars per capita in usage
• 𝐴𝑑𝑣𝑖, 𝐷𝑒𝑣𝑖 −dummy variables for advanced and developed
• 𝛼𝑖–can capture country-specific effects
• 𝐸𝑖𝑡 −stochastic error term
The Base Line Specification
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12. • Applied Model : Random Effect Model
• The main hypothesis : more renewable energy
less CO2
Extension of the initial model , including:
• Time trend
• Geographical and seasonal factors
• Threshold effect ( Chiu and Changes’ hypothesis)
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13. •1% increase in renewable energy consumption reduces
CO2 emissions by approximately 2%
• The model proves Chui and Change’s hypothesis – minimal
threshold 8%
• Above the threshold the effect is slightly above 10%
• The forest area does not have much explanatory power
The received results
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14. • CO2 positively correlated with the country’s economic development.
73%more in advanced countries than in developing countries
• If cars per capita indicator increases by 0.1 units, carbon dioxide
level will go up by 7.4%
• It is possible for developing countries to change the performance of
Environmental Kuznets Curve
The received results
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15. • Reduce the number of carbon-fired plants
• Shift to larger share of renewable energy utilization
However, policies in this field should be:
• Country-specific
• Implemented gradually
Recommendations
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16. 16

17. Questions, recommendations,
or short speeches !?
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