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Empirical Study of Climate Finance

  • Antonio A. Romano
  • Giuseppe Scandurra
  • Alfonso Carfora
  • Monica Ronghi
Chapter
Part of the SpringerBriefs in Climate Studies book series (BRIEFSCLIMATE)

Abstract

The chapter proposes one of the possible approaches to investigate whether developing countries can progress towards more environmentally sustainable development using the flow of funds provided by developed (or donor) countries by increasing the resilience of their environmental, social and economic systems to either endogenous or exogenous shocks. After a description of the observed data, there will follow a construction of a composite indicator capable of providing a quantitative measure of the environmental performance of a country related to other variables that are able to describe social and economic particularities. In this way, it is possible to individuate a way capable of giving a measure of the repercussion of the financial flows on combating environmental degradation seen through the most important components of the increase in global warming. Our results contribute to the debate on the vulnerability and resilience of receiving countries as part of the UN Framework Convention on Climate Change agreement.

Keywords

Greenhouse gas Environmental pollution index Quantile regression Clustered data AidData Energy generation Biosphere protection 

References

  1. Aflaki S, Basher SA, Masini A (2014) Does economic growth matter? Technology-push, demand-pull and endogenous drivers of innovation in the renewable energy industry. HEC Paris Research Paper No. MOSI-2015-1070Google Scholar
  2. Bhattacharyya SC (2013) Financing energy access and off-grid electrification: a review of status, options and challenges. Renew Sust Energ Rev 20:462–472CrossRefGoogle Scholar
  3. Cecelski E (2001) Gender perspectives on energy for CSD-9. Draft position paper including recommendations proposed by the ENERGIA Support Group and the CSD NGO Women’s Caucus. Available at http://www.energia.org/resources/papers/csdposition.html
  4. Desjardins S, Gomes R, Pursnani P, West C (2014) Accelerating access to energy: lessons learned from efforts to build inclusive energy markets in developing countries. http://www.shellfoundation.org/ShellFoundation.org_new/media/Shell-Foundation-Reports/Access_to_Energy_Report_2014.pdf. Accessed 14 Jan 2016
  5. Elnakat A, Gomez JD (2015) Energy engenderment: an industrialized perspective assessing the importance of engaging women in residential energy consumption management. Energy Policy 82:166–177. doi: 10.1016/j.enpol.2015.03.014 CrossRefGoogle Scholar
  6. Kanagawa M, Nakata T (2007) Analysis of the energy access improvement and its socio-economic impacts in rural areas of developing countries. Ecol Econ 62(2):319–329CrossRefGoogle Scholar
  7. Kanagawa M, Nakata T (2008) Assessment of access to electricity and the socio-economic impacts in rural areas of developing countries. Energy Policy 36(6):2016–2029CrossRefGoogle Scholar
  8. Karekezi, S., & Kithyoma, W. (2002). Renewable energy strategies for rural Africa: is a PV-led renewable energy strategy the right approach for providing modern energy to the rural poor of sub-Saharan Africa? Energy Policy, 30(11–12), 1071–1086. doi:http://dx.doi.org/10.1016/S0301-4215(02)00059-9
  9. Karki SK, Mann MD, Salehfar H (2005) Energy and environment in the ASEAN: challenges and opportunities. Energy Policy 33(4):499–509. doi:http://dx.doi.org/10.1016/j.enpol.2003.08.014
  10. Kaygusuz, K. (2012). Energy for sustainable development: a case of developing countries. Renew Sust Energ Rev, 16(2), 1116–1126. doi:http://dx.doi.org/10.1016/j.rser.2011.11.013
  11. Khennas S (2012) Understanding the political economy and key drivers of energy access in addressing national energy access priorities and policies: African perspective. Energy Policy 47(Supplement 1):21–26. doi:http://dx.doi.org/10.1016/j.enpol.2012.04.003
  12. Marques AC, Fuinhas JA (2012) Are public policies towards renewables successful? Evidence from European countries. Renew Energy 44:109–118CrossRefGoogle Scholar
  13. Marques AC, Fuinhas JA, Manso JP (2011) A quantile approach to identify factors promoting renewable energy in European countries. Environ Resource Econ 49:351–366CrossRefGoogle Scholar
  14. Martinot E, Chaurey A, Lew D, Moreira JR, Wamukonya N (2002) Renewable energy markets in developing countries. Annu. Rev. Energy Environ 27:309–348CrossRefGoogle Scholar
  15. Mulugetta Y (2008) Human capacity and institutional development towards a sustainable energy future in Ethiopia. Renew Sust Energ Rev 12:1435–1450CrossRefGoogle Scholar
  16. Neumayer E, Plümper T, Barthel F (2014) The political economy of natural disaster damage. Glob Environ Chang 24:8–19. doi:http://dx.doi.org/10.1016/j.gloenvcha.2013.03.011
  17. OECD (2008) Handbook on constructing composite indicators: methodology and user guide. OECD, ParisGoogle Scholar
  18. Onyeji I, Bazilian M, Nussbaumer P (2012) Contextualizing electricity access in sub-Saharan Africa. Energy Sustain Dev 16(4):520–527CrossRefGoogle Scholar
  19. Parente PM, Santos Silva J (2016) Quantile regression with clustered data. J Econ Methods 5(1):1–15. doi: 10.1515/jem-2014-0011 CrossRefGoogle Scholar
  20. Pfeiffer B, Mulder P (2013) Explaining the diffusion of renewable energy technology in developing countries. Energy Econ 40:285–296. doi:http://dx.doi.org/10.1016/j.eneco.2013.07.005
  21. R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. URL https://www.R-project.org/
  22. Rao MN, Reddy BS (2007) Variations in energy use by Indian households: an analysis of micro level data. Energy 32(2):143–153. doi:http://dx.doi.org/10.1016/j.energy.2006.03.012
  23. Romano AA, Scandurra G (2016) Divergences in the determinants of investments in renewable energy sources: hydroelectric vs. other renewable sources. J Appl Stat 43(13):2363–2376. doi: 10.1080/02664763.2016.1163526 CrossRefGoogle Scholar
  24. Romano AA, Scandurra G, Carfora A (2015) Probabilities to adopt feed in tariff conditioned to economic transition: a scenario analysis. Renew Energy 83:988–997CrossRefGoogle Scholar
  25. Romano AA, Scandurra G, Carfora A, Pansini RV (2016) Assessing the determinants of SIDS’ pattern toward sustainability: a statistical analysis. Energy Policy. Forthcoming. doi: 10.1016/j.enpol.2016.03.042
  26. Saisana M, Saltelli A (2011) Rankings and ratings: instructions for use. Hague J Rule Law 3(2):247–268CrossRefGoogle Scholar
  27. Sam A, Syed Abul B, Andrea M (2016) Does economic growth matter? Technology-push, demand-pull and endogenous drivers of innovation in the renewable energy industry. MPRA – Working paper. https://mpra.ub.uni-muenchen.de/69773/1/MPRA_paper_69773.pdf
  28. Thomas C, Rolls J, Tennant T (2000) The GHG indicator: UNEP guidelines for calculating greenhouse gas emissions for businesses and non-commercial organisations. UNEP, ParisGoogle Scholar
  29. Tierney MJ, Nielson DL, Hawkins DG, Timmons Roberts J, Findley MG, Powers RM, Parks B, Wilson SE, Hicks RL (2011) More dollars than sense: refining our knowledge of development finance using AidData. World Dev 39(11):1891–1906CrossRefGoogle Scholar
  30. Toklu E, Guney MS, Isik M et al (2010) Energy production, consumption, policies and recent developments in Turkey. Renew Sust Energ Rev 1:1172–1186CrossRefGoogle Scholar
  31. Urmee T, Md A (2016) Social, cultural and political dimensions of off-grid renewable energy programs in developing countries. Renew Energy 93:159–167. doi: 10.1016/j.renene.2016.02.040 CrossRefGoogle Scholar
  32. Vidoli, F., Fusco, E. (2015). Compind: composite indicators functions. R package version 1.1. https://CRAN.R-project.org/package=Compind
  33. Walekhwa PN, Mugisha J, Drake L (2009) Biogas energy from family-sized digesters in Uganda: critical factors and policy implications. Energy Policy 37(7):2754–2762. doi:http://dx.doi.org/10.1016/j.enpol.2009.03.018
  34. Zhao SX, Chan RC, Chan NYM (2012) Spatial polarization and dynamic pathways of foreign direct investment in China 1990–2009. Geoforum 43(4):836–850CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Antonio A. Romano
    • 1
  • Giuseppe Scandurra
    • 1
  • Alfonso Carfora
    • 2
  • Monica Ronghi
    • 1
  1. 1.Department of Management Studies and Quantitative MethodsUniversity of Naples “Parthenope”NaplesItaly
  2. 2.Italian Revenue AgencyRomeItaly

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