Determinants of Renewable Energy Technology Adoption in Developing Countries

1. Determinants of Renewable Energy Technology Adoption in Developing Countries Birte PohlGIGA German Institute of Global and Area Studies International Energy Workshop (IEW)University of Cape Town, South Africa

2. Outline • Motivation and Research Questions • Stylized Facts • Related Literature • Econometric Analysis • Summary of Findings • Policy Implications and Conclusions Birte Pohl – Renewable Energy Technology Adoption in DCs

3. Motivation and Research Questions • no binding emission reduction targets for developing countries (DCs) • many DCs already produce electricity from renewable energy sources such as hydropower or non-hydropower (biomass, geothermal, solar, wind) • analysis of environmental technological change has mainly been carried out in a developed country context • the technological change process is likely to differ across countries (Del Río González 2009)  Which factors drive renewable energy technology adoption in the power sector of DCs?  How can the adoption of these technologies in DCs be promoted? Birte Pohl – Renewable Energy Technology Adoption in DCs

4. Stylized Facts Table 1: Importance of Hydro and Non-Hydropower across World Regions Data Source: EIA. Notes: Hydropower includes small and large hydropower. Non-hydropower includes biomass, geothermal, solar and wind. Birte Pohl – Renewable Energy Technology Adoption in DCs

5. Stylized Facts Figure 1: Share of Electricity Generated from Hydro and Non-Hydropower Data Source: EIA. Birte Pohl – Renewable Energy Technology Adoption in DCs

6. Stylized Facts Figure 2: Per Capita Electricity Generation from Conventional Energy Sources, Hydropower and Non-Hydropower in kWh Per Capita Data Source: EIA. Birte Pohl – Renewable Energy Technology Adoption in DCs

7. Related Literature Brunnschweiler (2010), Finance for Renewable Energy: An Empirical Analysis of Developing and Transition Economies • power sector • non-OECD countries, 1980-2006 • Random Effects, GMM • finding: financial development has a significant positive effect on renewable energy technology adoption Birte Pohl – Renewable Energy Technology Adoption in DCs

8. What is new? My paper differs with regard to • country sample • dependent variable (aggregate: non-hydropower) • control variables • econometric specification Birte Pohl – Renewable Energy Technology Adoption in DCs

9. Data • to be explained: electricity production from non-hydropower (kWh per capita), provided by Energy Information Administration (EIA) • sample: 116 developing countries (excl. 21 transition countries as defined by IMF 2000) • period: 1980-2009 Birte Pohl – Renewable Energy Technology Adoption in DCs

10. Data Descriptive Statistics on Renewable Energy Production, 1980-2009 Table 2: Per Capita Generation and Share of Aggregated Non-Hydropower, Biomass, Geothermal, Solar, and Wind Data Source: EIA. Birte Pohl – Renewable Energy Technology Adoption in DCs

11. Data What drives the adoption of non-hydropower technology to produce electricity in DCs? • level of economic development (≈ energy demand) • policies • substitutes and opportunity costs • general drivers of technology adoption • governance and institutions Birte Pohl – Renewable Energy Technology Adoption in DCs

12. Data Focus: Policies • renewable energy policy targets for power generation: biomass, geothermal, solar, wind, multiple renewable energy • sector: electricity • policy types: • economic instruments • policy support • regulatory instruments • research, development and deployment • information and education • voluntary approaches Data Source: IEA/IRENA Global Renewable Energy Policies and Measures Database Birte Pohl – Renewable Energy Technology Adoption in DCs

13. Data Descriptive Statistics on Control Variables, 1980-2009 Data Sources: EIA, World Bank, IEA/IRENA, Kaufmann et al. Birte Pohl – Renewable Energy Technology Adoption in DCs

14. Econometric Model & Methodology General Model • regression analysis, level and log specification • Fixed Effects • exclusion of outliers based on standardized residuals of first specification (1% level ≈ 2.58) Birte Pohl – Renewable Energy Technology Adoption in DCs

15. Results: Level Specification Birte Pohl – Renewable Energy Technology Adoption in DCs

16. Results: Level Specification Birte Pohl – Renewable Energy Technology Adoption in DCs

17. Results: Log Specification Birte Pohl – Renewable Energy Technology Adoption in DCs

18. Results: Log Specification Birte Pohl – Renewable Energy Technology Adoption in DCs

19. Results: Other Specifications regression using biomass, geothermal solar, and wind (kWh per capita) as dependent variables • biomass: negative association for biomass policy (but data includes only two countries with such a policy); positive correlation with multiple policies • geothermal: positive, significant effect of geothermal policies • solar: no association at all • wind: positive, significant association with wind and multiple policies Birte Pohl – Renewable Energy Technology Adoption in DCs

20. Summary of Findings • richer countries (with higher energy demand) generally invest more in non-hydropower • renewable energy policies, especially for wind power and those that target multiple renewable energy sources, seem to support investments in non-hydropower • countries that have higher shares of hydropower electricity less often invest in non-hydropower • positive association between non-hydropower generation and open trade markets • shortcomings: indirect approach, not all policies included, general technology adoption measures are not specific to the renewable energy sector Birte Pohl – Renewable Energy Technology Adoption in DCs

21. Policy Implications and Conclusions • making countries switch to renewable energy technology is likely to require deliberate concerted efforts and context-specific policies • some policies seem to be effective • spillovers effects may be important Birte Pohl – Renewable Energy Technology Adoption in DCs

22. Thank you for listening. Birte Pohl – Renewable Energy Technology Adoption in DCs

23. Appendix Birte Pohl – Renewable Energy Technology Adoption in DCs

24. Stylized Facts Renewable Energy in DCs Hydropower • wide-spread adoption: generated by 80% of all DCs in sample • average share of total electricity (2009): 38% (14% weighted with total country electricity production) Non-hydropower (biomass, geothermal, solar, and wind) • generated by about 44% of DCs in sample • average share of total electricity (2009): 1.6% • most important: biomass, geothermal • less common: wind, solar Data Source: EIA Birte Pohl – Renewable Energy Technology Adoption in DCs

25. Stylized Facts Figure 3: Relationship between Per Capita Electricity Generation from Non-Hydropower in kWh and GDP Per Capita (2009) Data Source: EIA. Birte Pohl – Renewable Energy Technology Adoption in DCs

26. Biomass Birte Pohl – Renewable Energy Technology Adoption in DCs

27. Geothermal Birte Pohl – Renewable Energy Technology Adoption in DCs

28. Solar Birte Pohl – Renewable Energy Technology Adoption in DCs

29. Wind Birte Pohl – Renewable Energy Technology Adoption in DCs