1. Determinants of Renewable Energy Deployment – Evidence for Developing Countries 1980–2008 2 nd EntDekEn Meeting, Hamburg, 10 October 2011 Birte Pohl (GIGA), Michael Jakob (PIK), Steffen Schlömer (PIK)

2. 13.06.20162 Motivation & Research Question What are the drivers and barriers to RET uptake in the power sector of developing countries? Why is this important? –Power sector accounts for 41% of global CO2 emissions –Growth of emissions in recent years can almost exclusively be attributed to developing countries –Likely to grow further with economic development progressing –RETs are a key mitigation technology and have multiple public co-benefits –Developers mostly sit in industrialized countries -> cross- country diffusion required

3. 13.06.20163 Theoretical Background (1/2) Many studies of cross-country technology diffusion –Focused on „success stories“, i.e. technologies that been widely diffused and caused „global change“ –Grounded in „new growth theory“, where technological innovation is the engine of growth –Strong focus technology supply side (openness and IPRs) –„Lately“, more focus on demand side (absorptive capacity, appropriate technologies, local attractiveness, capability to adopt) Several key determinants identified: –Openess to trade and FDI –Distance between source and recipient –Labour turnover –Human capital –Domestic R&D investments –Sectoral specialization –Deployment of predecessor technologies –Governance

4. 13.06.20164 Theoretical Background (2/2) RETs likely differ from conventional „success stories“ Attractiveness derives to considerable degree from „positive externalities“ and related institutions –Climate change mitigation (reduced GHG emissions) –Improved public health (reduced local air pollution) –Increased energy security (reduced fossil fuel imports) –Improved energy access (decentralized production) Finance considered as further key determinant in DCs Other sector-specifics and factor endowments relevant

5. 13.06.20165 Most Closely Related Literature Brunnschweiler (2010) examines the role of financial sector development for RET adoption 119 non-OECD countries, 1980-2006 finds that financial development has a significant positive effect on RET and non-hydropower renewables Popp et al. (2011) examines the effect of RET-specific knowledge on deployment 26 OECD countries, 1991-2004 finds a small but significant positive effect

6. 13.06.20166 Econometric Model First model: per capita electricity generation from RET (hydro and non-hydropower) in 1000 kWh per capita in country j in year t Second model: per capita electricity generation from non- hydropower (geothermal, wind, solar, tide and wave, biomass and waste) in 1000 kWh per capita in country j in year t (1) (2) Table 1: Summary of RET Electricity Generation, 1980-2008 Data Source: EIA, share

7. 13.06.20167 Control Variables I Commonly discussed drivers of technology adoption –level of economic development (log of GDP per capita) –openness (trade, FDI) –human capital endowments (enrollment rate, completion rate) –level of financial development (assets, liabilities, credit) Environmental externalities and related regulatory institutions associated with RET –adoption of the Kyoto Protocol (kyoto dummy) –feed-in tariff –quality of the environmental regulatory system (regulation, 4 quartiles) –local pollution (pm10, 4 quartiles)

8. 13.06.20168 Control Variables II Table 2: Summary Statistics of Control Variables, 1980–2008

9. 13.06.20169 Econometric Methodology Random Effects (RE) and Fixed Effecs (FE) estimation RE: assumption that the unobserved effect is purely random and uncorrelated with the explanatory variables FE: accounts for unobserved heterogeneity across countries, requires the assumption of strict exogeneity to hold hausman test (Hausman 1978) to test whether the country-specific effects are uncorrelated with the regressors (appropriateness of the RE model)  Our analysis shows that in some specifications RE is consistent and efficient, while in others not. In this case, the FE results should be preferred.

10. 13.06.201610 Results I Baseline Model

11. 13.06.201611 Results II Openness

12. 13.06.201612 Results III Human Capital

13. 13.06.201613 Results IV Financial Development

14. 13.06.201614 Results V Feed-in Tariff

15. 13.06.201615 Results VI Regulation

16. 13.06.201616 Results VII PM10 concentration as a measure of regulation

17. 13.06.201617 Results VIII Sensitivity Analysis I

18. 13.06.201618 Results IX DFITS statistics (Belsley et al. 1980) shows that Paraguay and Bhutan have unusual influence on estimates using RET as dependent variable Exclusion of these countries yields the following results: coefficients of trade and enrollment rate are not significant anymore coefficient of assets is negative, but not significant anymore Sensitivity Analysis II

19. 13.06.201619 Results X: Summary RET is positively and significantly associated with LGDP Kyoto Protocol has had a positive impact on RET use Non-hydro power is positively and significantly related to LGDP, trade, assets and feed-in tariff Unexpected findings: Financial development: negative or statistically insignificant coefficients (in contrast to Brunnschweiler 2010) Broadly based measures of regulation are not significant

20. 13.06.201620 Conclusions First cross-country analysis regarding the determinants of RET adoption in developing countries Generall assessment of various factors influencing the adoption of RET Highlights the sensitivity of various explanatory variables  Identifies a need for further analysis

21. 13.06.201621 Discussion Data availability and selection Sensitivity of explanatory variables (sample selection, model specification) Small explanatory power of some models

22. 13.06.201622 Appendix I Table A1: Definition of Control Variables

23. 13.06.201623 Appendix II Financial Development