Environment, Development and Sustainability

, Volume 18, Issue 1, pp 73–94 | Cite as

Evaluating households’ preferences regarding reducing power outages in rural areas: cases in the Ganges Floodplain in Bangladesh

  • Johannes Breit
  • Satoru Komatsu
  • Shinji Kaneko
  • Partha Pratim Ghosh


This paper investigates household preferences regarding an improved supply of electricity in rural Bangladesh, where the expansion of stable electricity is an urgent policy issue. The paper examines household preferences regarding reductions in the frequency and duration of power outages. It also examines prior notification mechanisms that do not necessarily provide an increased supply of electricity but that allow households to prepare for potential power failures. A questionnaire survey designed as a choice experiment was applied to households to elicit preferences. The econometric analysis reveals that villagers prefer a reduction in both the frequency and duration of power outages and a 1-day prior notification of power outages. There are slight disparities in preferences according to the season and the timing of improvements (e.g., summer or winter and all day or peak hours). Thus, the present study may be beneficial for policymakers when considering the provision of electricity supply improvements in rural areas in exchange for slight increases in electricity tariffs.


Preference Electricity supply Power outage Prior notification Bangladesh 



The authors thank the editors and four anonymous referees for their constructive comments and suggestions to improve the quality of an earlier version of the manuscript. This research was supported by the Ministry of Education, Culture, Sports, Science, and Technology, Japan, Grant-in-Aid for Scientific Research (No. 22310030, 23710057, 25257102, 26740057); Strategic Funds for the Promotion of Science and Technology, “Global Environmental Leaders Education Program for Designing a Low-Carbon Society”; and the Environment Research and Technology Development Fund of the Ministry of Environment, Japan, “Research Project to Establish a Methodology to Evaluate Middle to Long Term Environmental Policy Options toward Asian Low-carbon Societies (S-6).” The authors greatly appreciate the assistance and cooperation of field investigators, survey respondents, and data entry personnel.

Conflict of interest

The authors do not have any conflicts of interest in terms of financial or personal involvement that may influence the judgments expressed in this manuscript.


  1. Abdullah, S., & Jeanty, P. W. (2011). Willingness to pay for renewable energy: Evidence from a contingent valuation survey in Kenya. Renewable and Sustainable Energy Reviews, 15, 2974–2983.CrossRefGoogle Scholar
  2. Abdullah, S., & Mariel, P. (2010). Choice experiment study on the willingness to pay to improve electricity services. Energy Policy, 38, 4570–4581.CrossRefGoogle Scholar
  3. Abdullah, S., & Markandya, A. (2012). Rural electrification programmes in Kenya: Policy conclusions from a valuation study. Energy for Sustainable Development, 16, 103–110.CrossRefGoogle Scholar
  4. Ahamad, M., & Tanin, F. (2013). Next power generation-mix for Bangladesh: Outlook and policy priorities. Energy Policy, 60, 272–283.CrossRefGoogle Scholar
  5. Ahmed, F., Al Amin, A. Q., Hasanuzzaman, M., & Saidur, R. (2013a). Alternative energy resources in Bangladesh and future prospect. Renewable and Sustainable Energy Reviews, 25, 698–707.CrossRefGoogle Scholar
  6. Ahmed, F., Trimble, C., & Yoshida, N. (2013). The transition from underpricing residential electricity in Bangladesh: Fiscal and distributional impacts. World Bank report number: 76411-BD. World Bank.Google Scholar
  7. Alam, M. S., Kabir, E., Rahman, M. M., & Chowdhury, M. A. K. (2004). Power sector reform in Bangladesh: Electricity distribution system. Energy, 29(11), 1773–1783.CrossRefGoogle Scholar
  8. Bangladesh Bureau of Statistics, BBS. (2006). Population census-2001 Zila series. Falidpur, Zila: Bangladesh Bureau of Statistics.Google Scholar
  9. BBS. (2006a). Population census-2001 Zila series. Jhenaidah, Zila: Bangladesh Bureau of Statistics.Google Scholar
  10. BBS. (2006b). Population Census-2001 Zila Series. Magura, Zila: Bangladesh Bureau of Statistics.Google Scholar
  11. BBS (2011a). Statistical yearbook of Bangladesh 2010. Dhaka: Bangladesh Bureau of Statistics.Google Scholar
  12. BBS (2011b). Report of the household income and expenditure survey 2010. Dhaka: Bangladesh Bureau of Statistics.Google Scholar
  13. Beenstock, M., Goldin, E., & Haitovsky, Y. (1998). Response bias in a conjoint analysis of power outages. Energy Economics, 20, 135–156.CrossRefGoogle Scholar
  14. Bhandari, R., & Stadler, I. (2011). Electrification using solar photovoltaic systems in Nepal. Applied Energy, 88(2), 458–465.CrossRefGoogle Scholar
  15. BPDB (2012). Annual report 2010–2011. Bangladesh Power Development Board.Google Scholar
  16. BTRC (2013). Mobile phone subscribers in Bangladesh December, 2013. Bangladesh Telecommunication Regulatory Commission, http://www.btrc.gov.bd/content/mobile-phone-subscribers-bangladesh-december-2013. Accessed March 11, 2014.
  17. Carlsson, F., & Martinsson, P. (2007). Willingness to pay among Swedish households to avoid power outages: A random parameter Tobit model approach. Energy Journal, 28, 75–89.CrossRefGoogle Scholar
  18. Carlsson, F., & Martinsson, P. (2008). Does it matter when a power outage occurs? A choice experiment study on the willingness to pay to avoid power outages. Energy Economics, 30, 1232–1245.CrossRefGoogle Scholar
  19. Carlsson, F., Martinsson, P., & Akay, A. (2011). The effect of power outages and cheap talk on willingness to pay to reduce outages. Energy Economics, 33, 790–798.CrossRefGoogle Scholar
  20. Daly, A., Hess, S., & Train, K. (2012). Assuring finite moments for willingness to pay in random coefficient models. Transportation, 39, 19–31.CrossRefGoogle Scholar
  21. DESCO (2013). Load shedding schedule, https://www.desco.org.bd/index.php?page=load-shedding. Accessed December 12, 2013.
  22. DPDC (2013). Load shedding, http://www.dpdc.org.bd/dpdc/loadsheddingsearch.php. Accessed December 12, 2013.
  23. Government of the People’s Republic of Bangladesh (2000). Vision statement and policy statement on power sector Reforms. Power Division, Ministry of Energy and Mineral Resources.Google Scholar
  24. Green, W. H. (2007). NLOGIT 4.0. Econometric Software Inc.Google Scholar
  25. Hanley, N., Colombo, S., Tinch, D., Black, A., & Aftab, A. (2006). Estimating the benefits of water quality improvements under the Water Framework Directive: Are benefits transferable? European Review of Agricultural Economics, 33(3), 391–413.CrossRefGoogle Scholar
  26. IEA (2012). WEO-2012 new electricity access Database.Google Scholar
  27. Islam, A., Chan, E.-S., Taufiq-Yapa, Y. H., Mondal, M. A. H., Moniruzzaman, M., & Mridha, M. (2014). Energy security in Bangladesh perspective—An assessment and implication. Renewable and Sustainable Energy Reviews, 32, 154–171.CrossRefGoogle Scholar
  28. Kaneko, S., Komatsu, S., & Ghosh, P. P. (2012). Rural electrification in Bangladesh: Implications for climate change mitigation. In R. Fujikura & T. Toyota (Eds.), Climate change mitigation and International Development Cooperation (pp. 202–226). London: Routledge.Google Scholar
  29. Khan, I., Alam, F., & Alam, Q. (2013). The global climate change and its effect on power generation in Bangladesh. Energy Policy, 61, 1460–1470.CrossRefGoogle Scholar
  30. Komatsu, S., Kaneko, S., Ghosh, P. P., & Morinaga, A. (2013). Determinants of user satisfaction with solar home systems in rural Bangladesh. Energy, 61, 52–58.CrossRefGoogle Scholar
  31. Komatsu, S., Kaneko, S., Shrestha, R. M., & Ghosh, P. P. (2011). Nonincome factors behind the purchase decisions of solar home systems in rural Bangladesh. Energy for Sustainable Development, 15(3), 284–292.CrossRefGoogle Scholar
  32. Layton, D., & Moeltner, K. (2005). The cost of power outages to heterogeneous households: An application of gamma-lognormal distribution. In A. Alberini & S. Riccardo (Eds.), Application of simulation method in environmental resource economics (pp. 35–54). Dordrecht: Springer.CrossRefGoogle Scholar
  33. Lim, K. M., Lim, S. Y., & Yoo, S. H. (2014). Estimating the economic value of residential electricity use in the Republic of Korea using contingent valuation. Energy, 64, 601–606.CrossRefGoogle Scholar
  34. Louviere, J. J., Hensher, D. A., & Swait, J. D. (2000). Stated choice methods: Analysis and application. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  35. Mondal, M. A. H., Boie, W., & Denich, M. (2010a). Future demand scenarios of Bangladesh power sector. Energy Policy, 38(11), 7416–7426.CrossRefGoogle Scholar
  36. Mondal, M. A. H., Denich, M., & Vlek, P. L. G. (2010b). The future choice of technologies and co-benefits of CO2 emission reduction in Bangladesh power sector. Energy, 35(12), 4902–4909.CrossRefGoogle Scholar
  37. Ohdoko, T., Komatsu, S., & Kaneko, S. (2013). Residential preferences for stable electricity supply and a reduction in air pollution risk: A benefit transfer study using choice modeling in China. Environmental Economics and Policy Studies, 15(3), 309–328.CrossRefGoogle Scholar
  38. Pepermans, G. (2011). The value of continuous power supply for Flemish households. Energy Policy, 39, 7853–7864.CrossRefGoogle Scholar
  39. Rahman, M. M., Paatero, J. V., Poudyal, A., & Lahdelma, R. (2013). Driving and hindering factors for rural electrification in developing countries: Lessons from Bangladesh. Energy Policy, 61, 840–851.CrossRefGoogle Scholar
  40. REB (2009). Annual report 2008–2009, Rural Electrification Board.Google Scholar
  41. REB (2013). REB website, http://www.reb.gov.bd/index.php. Accessed December 11, 2013.
  42. Taniguchi, M., & Kaneko, S. (2009). Operational performance of the Bangladesh rural electrification program and its determinants with a focus on political interference. Energy Policy, 37(6), 2433–2439.CrossRefGoogle Scholar
  43. Train, K. E. (2006). Discrete choice methods with simulation (2nd ed.). Cambridge: Cambridge University Press.Google Scholar
  44. World Bank (2013). Enterprise surveys: What businesses experience. http://www.enterprisesurveys.org/data/exploreTopics/Infrastructure#–1 Accessed March 11, 2014.

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Johannes Breit
    • 4
  • Satoru Komatsu
    • 1
  • Shinji Kaneko
    • 2
  • Partha Pratim Ghosh
    • 3
  1. 1.School of Global Humanities and Social SciencesNagasaki UniversityNagasakiJapan
  2. 2.Graduate School for International Development and CooperationHiroshima UniversityHigashi-HiroshimaJapan
  3. 3.Grameen CommunicationsDhakaBangladesh
  4. 4.Becker Büttner Held ConsultingMunichGermany

Personalised recommendations