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Energy Efficiency

, Volume 11, Issue 3, pp 663–681 | Cite as

The impact of microhydroelectricity on household welfare indicators

  • Mary KarumbaEmail author
  • Edwin Muchapondwa
Original Article
Part of the following topical collections:
  1. Energy and Climate Economic Modelling

Abstract

The use of small-scale off-grid renewable energy for rural electrification is now seen as part of the sustainable energy solutions. The expectation from such small-scale investment is that it can meet the basic energy needs of a household and subsequently improve some aspects of household welfare. However, these stated benefits remain largely hypothetical because there are data and methodological challenges in existing literature attempting to isolate such impact. This paper uses field data from microhydro schemes in Kenya, and propensity score matching technique to demonstrate such an impact. We find that on average, households connected to microhydroelectricity consume 1.5 l less of kerosene per month compared to households without any such electricity connection. In addition, non-connected households spend 0.92 USD more for recharging their cell phone batteries per month in comparison to those who were using microhydroelectricity service. Finally, school children from households that are connected to microhydroelectricity were found to devote 43 min less on evening studies compared to those without electricity. The findings provide interesting insights to some of the claims made for or against use of off grid renewable energy for rural electrification.

Keywords

Microhydro Rural electrification Impact Kenya 

JEL classifications

C21 Q01 Q42 

Notes

Acknowledgments

The authors are grateful to the Environment for Development (EfD) for funding the fieldwork for this study, and the enumerators and households in the three counties of the Republic of Kenya that participated in this study. We also acknowledge financial support in preparation of this article from Economic Modelling for Climate-Energy Policy (ECOCEP)

References

  1. Abu-Sharkh, S., Arnold, R., Kohler, J., Li, R., Markvart, T., Ross, J., Steemers, K., Wilson, P., & Yao, R. (2006). Can microgrids make a major contribution to UK energy supply? Renewable and Sustainable Energy Reviews, 10(2), 78–127.  https://doi.org/10.1016/j.rser.2004.09.013.CrossRefGoogle Scholar
  2. Austin, P. C. (2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioural Research, 46(3), 399–424.  https://doi.org/10.1080/00273171.2011.568786.CrossRefGoogle Scholar
  3. Barnes, D. F., & Binswanger, H. P. (1986). Impact of rural electrification and infrastructure on agricultural changes, 1966-1980. Economic and Political Weekly, 21(1), 26–34.Google Scholar
  4. Bensch, G., Kluve, J., & Peters, J. (2011). Impacts of rural electrification in Rwanda. Journal of Development Effectiveness, 3(4), 567–588.  https://doi.org/10.1080/19439342.2011.621025.CrossRefGoogle Scholar
  5. Bensch, G., Peters, J., & Sievert, M. (2012). Fear of the dark? How access to electric lighting affects security attitudes and nighttime activities in rural Senegal. Ruhr Economic Paper No. 369. https://ssrn.com/abstract=2159712 or  https://doi.org/10.2139/ssrn.2159712.
  6. Bernard, T. (2010). Impact analysis of rural electrification projects in Sub-Saharan Africa. The World Bank Research Observer, 27(1), 33–35.Google Scholar
  7. Caliendo, M., & Kopeinig, S. (2008). Some practical guidance for the implementation of propensity score matching. Journal of Economic Surveys, 22(1), 31–72.  https://doi.org/10.1111/j.1467-6419.2007.00527.x.CrossRefGoogle Scholar
  8. Casillas, C. E., & Kammen, D. M. (2011). The delivery of low-cost, low-carbon rural energy services. Energy Policy, 39(8), 4520–4528.  https://doi.org/10.1016/j.enpol.2011.04.018.CrossRefGoogle Scholar
  9. Dinkelman, T. (2011). The effects of rural electrification on employment: New evidence from South Africa. The American Economic Review, 101(7), 3078–3108.  https://doi.org/10.1257/aer.101.7.3078.CrossRefGoogle Scholar
  10. Gangl, M. (2004). RBOUNDS: Stata module to perform Rosenbaum sensitivity analysis for average treatment effects on the treated. Statistical Software Components, Boston College Department of Economics. https://econpapers.repec.org/software/bocbocode/s438301.htm. Accessed 3 Dec 2017.
  11. Garrido, M. M., Kelley, A. S., Paris, J., Roza, K., Meier, D. E., Morrison, R. S., & Aldridge, M. D. (2014). Methods for constructing and assessing propensity scores. Health Services Research, 49(5), 1701–1720.  https://doi.org/10.1111/1475-6773.12182.CrossRefGoogle Scholar
  12. Hirmer, S., & Cruickshank, H. (2014). The user-value of rural electrification: An analysis and adoption of existing models and theories. Renewable and Sustainable Energy Reviews, 34, 145–154.  https://doi.org/10.1016/j.rser.2014.03.005.CrossRefGoogle Scholar
  13. International Energy Agency. (2015). World energy outlook data base. Available at http://www.worldenergyoutlook.org/resources/energydevelopment/energyaccessdatabase/. Accessed on 5th Dec 2016.
  14. Jacobson, A. (2007). Connective power: Solar electrification and social change in Kenya. World Development, 35(1), 144–162.CrossRefGoogle Scholar
  15. Khandker, S. R., Barnes, D. F., and Samad, H. A. (2009). Welfare impacts of rural electrification: A case study from Bangladesh. World Bank Policy Research Working Paper Series, no. 4859. The World BankGoogle Scholar
  16. Khandker, S. R., Barnes, D. F., & Samad, H. A. (2012). The welfare impacts of rural electrification in Bangladesh. The Energy Journal, 33(1).  https://doi.org/10.5547/ISSN0195-6574-EJ-Vol33-No1-7.
  17. Khandker, S. R., Barnes, D. F., & Samad, H. A. (2013). Welfare impacts of rural electrification: A panel data analysis from Vietnam. Economic Development and Cultural Change, 61(3), 659–692.  https://doi.org/10.1086/669262.CrossRefGoogle Scholar
  18. Kirubi, C., Jacobson, A., Kammen, D. M., & Mills, A. (2009). Community based electric micro-grids can contribute to rural development: Evidence from Kenya. World Development, 37(7), 1208–1221.  https://doi.org/10.1016/j.worlddev.2008.11.005.CrossRefGoogle Scholar
  19. Kohlin, G., Sills, E. O., Pattanayak, S. K., and Wilfong, C. (2011). Energy, gender and development: What are the linkages? Where is the evidence?. World Bank Policy Research Working Paper no. 5800. The World BankGoogle Scholar
  20. Komatsu, S., Kaneko, S., & Ghosh, P. P. (2011). Are micro-benefits negligible? The implications of the rapid expansion of solar home systems (SHS) in rural Bangladesh for sustainable development. Energy Policy, 39(7), 4022–4031.  https://doi.org/10.1016/j.enpol.2010.11.022.CrossRefGoogle Scholar
  21. Madubansi, M., & Shackleton, C. (2006). Changing energy pro les and consumption patterns following electrification in five rural villages, South Africa. Energy Policy, 34(18), 4081–4092.  https://doi.org/10.1016/j.enpol.2005.10.011.CrossRefGoogle Scholar
  22. Madubansi, M., & Shackleton, C. (2007). Changes in fuelwood use and selection following electrification in the Bushbuckridge Lowveld, South Africa. Journal of Environmental Management, 83(4), 416–426.  https://doi.org/10.1016/j.jenvman.2006.03.014.CrossRefGoogle Scholar
  23. Matinga, M. N., & Annegarn, H. J. (2013). Paradoxical impacts of electricity on life in a rural South African village. Energy Policy, 58, 295–302.  https://doi.org/10.1016/j.enpol.2013.03.016.CrossRefGoogle Scholar
  24. Mondal, A. H., & Klein, D. (2011). Impacts of solar home systems on social development in rural Bangladesh. Energy for Sustainable Development, 15(1), 17–20.  https://doi.org/10.1016/j.esd.2010.11.004.CrossRefGoogle Scholar
  25. Munuswamy, S., Nakamura, K., & Katta, A. (2011). Comparing the cost of electricity sourced from a fuel cell-based renewable energy system and the national grid to electrify a rural health centre in India: A case study. Renewable Energy, 36(11), 2978–2983.  https://doi.org/10.1016/j.renene.2011.03.041.CrossRefGoogle Scholar
  26. Ngui, D., Mutua, J., Osiolo, H., & Aligula, E. (2011). Household energy demand in Kenya: An application of the linear approximate almost ideal demand system (LA-AIDs). Energy Policy, 39(11), 7084–7094.  https://doi.org/10.1016/j.enpol.2011.08.015.CrossRefGoogle Scholar
  27. Obermaier, M., Szklo, A., La Rovere, E. L., & Rosa, L. P. (2012). An assessment of electricity and income distributional trends following rural electrification in poor northeast Brazil. Energy Policy, 49, 531–540.  https://doi.org/10.1016/j.enpol.2012.06.057.CrossRefGoogle Scholar
  28. Rao, N. D. (2013). Does (better) electricity supply increase household enterprise income in India? Energy Policy, 57, 532–541.  https://doi.org/10.1016/j.enpol.2013.02.025.CrossRefGoogle Scholar
  29. Rollin, H., Mathee, A., Bruce, N., Levin, J., & Von Schirnding, Y. (2004). Comparison of indoor air quality in electrified and un-electrified dwellings in rural South African villages. Indoor Air, 14(3), 208–216.  https://doi.org/10.1111/j.1600-0668.2004.00238.x.CrossRefGoogle Scholar
  30. Rosenbaum, P. R. (2002). Attributing effect to treatment in matched observational studies. Journal of the American Statistical Association, 97(457), SpringerGoogle Scholar
  31. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.  https://doi.org/10.1093/biomet/70.1.41.MathSciNetCrossRefzbMATHGoogle Scholar
  32. Terrado, E., Cabraal, R. A., and Mukherjee, I. (2008). Designing sustainable off-grid rural electrification projects: principles and practices: Operational guidance for World Bank Group staff. World Bank. The Energy and Mining Sector Board.Google Scholar
  33. Van de Walle, D. P., Ravallion, M., Mendiratta, V., and Koolwal, G. B. (2013). Long-term impacts of household electrification in rural India. World Bank Policy Research Working Paper, 6527 Google Scholar
  34. Zhao, Z. (2008). Sensitivity of propensity score methods to the specifications. Economics Letters, 98(3), 309–319.  https://doi.org/10.1016/j.econlet.2007.05.010.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of EconomicsUniversity of Cape TownCape TownSouth Africa
  2. 2.Department of Business Administration, Technology and Social SciencesLuleå University of TechnologyLuleåSweden

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