IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v170y2022ics0301421522004700.html
   My bibliography  Save this article

Pre-paid meters and household electricity use behaviors: Evidence from Addis Ababa, Ethiopia

Author

Listed:
  • Beyene, Abebe D.
  • Jeuland, Marc
  • Sebsibie, Samuel
  • Hassen, Sied
  • Mekonnen, Alemu
  • Meles, Tensay H.
  • Pattanayak, Subhrendu K.
  • Klug, Thomas

Abstract

In low-income countries such as Ethiopia, pre-paid metering is often argued to alleviate several challenges with traditional electricity billing systems, including high non-payment rate, pilferage and fraud, administrative and enforcement costs for utilities, and inflexibility and incongruence of bills with poorer consumers' irregular income. Despite increasing adoption of this technology, few studies examine its causal impacts on household behaviour. This paper examines the impacts of pre-paid metering on electricity consumption, ownership of appliances, level of satisfaction, and cooking behaviour in Addis Ababa, the capital of Ethiopia. We employ propensity score matching and instrumental variable techniques to control for the non-random selection into pre-paid metering. Results indicate that pre-paid customers have significantly lower electricity consumption compared to those with traditional meters, and express greater satisfaction with utility service. This technology also has a positive, but modest and statistically insignificant impact on total appliance ownership, and a positive and significant impact on ownership of energy-efficient lights. Impacts are heterogeneous across customers, however: those who are more educated, who have higher income, and who do not share meters tend to reduce electricity use more. The results suggest that pre-paid meters have had positive impacts on households and the utility in Addis Ababa.

Suggested Citation

  • Beyene, Abebe D. & Jeuland, Marc & Sebsibie, Samuel & Hassen, Sied & Mekonnen, Alemu & Meles, Tensay H. & Pattanayak, Subhrendu K. & Klug, Thomas, 2022. "Pre-paid meters and household electricity use behaviors: Evidence from Addis Ababa, Ethiopia," Energy Policy, Elsevier, vol. 170(C).
  • Handle: RePEc:eee:enepol:v:170:y:2022:i:c:s0301421522004700
    DOI: 10.1016/j.enpol.2022.113251
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421522004700
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.enpol.2022.113251?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. B. Kelsey Jack & Grant Smith, 2015. "Pay as You Go: Prepaid Metering and Electricity Expenditures in South Africa," American Economic Review, American Economic Association, vol. 105(5), pages 237-241, May.
    2. Bao Jiayi & Ho Benjamin, 2015. "Heterogeneous Effects of Informational Nudges on Pro-social Behavior," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 15(4), pages 1619-1655, October.
    3. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    4. Aydin, Erdal & Brounen, Dirk & Kok, Nils, 2018. "Information provision and energy consumption: Evidence from a field experiment," Energy Economics, Elsevier, vol. 71(C), pages 403-410.
    5. Mwaura, Francis M., 2012. "Adopting electricity prepayment billing system to reduce non-technical energy losses in Uganda: Lesson from Rwanda," Utilities Policy, Elsevier, vol. 23(C), pages 72-79.
    6. Gideon Otchere-Appiah & Shingo Takahashi & Mavis Serwaa Yeboah & Yuichiro Yoshida, 2021. "The Impact of Smart Prepaid Metering on Non-Technical Losses in Ghana," Energies, MDPI, vol. 14(7), pages 1-16, March.
    7. Edem Maxwell Azila-Gbettor & Eli Ayawo Atatsi & Faith Deynu, 2015. "An Exploratory Study of Effects of Prepaid Metering and Energy Related Behaviour among Ghanaian Household," International Journal of Sustainable Energy and Environmental Research, Conscientia Beam, vol. 4(1), pages 8-21.
    8. Golumbeanu, Raluca & Barnes, Douglas, 2013. "Connection charges and electricity access in Sub-Saharan Africa," Policy Research Working Paper Series 6511, The World Bank.
    9. O'Sullivan, Kimberley C. & Stanley, James & Fougere, Geoffrey & Howden-Chapman, Philippa, 2016. "Heating practices and self-disconnection among electricity prepayment meter consumers in New Zealand: A follow-up survey," Utilities Policy, Elsevier, vol. 41(C), pages 139-147.
    10. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    11. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    12. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    13. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," CERT Discussion Papers 0706, Centre for Economic Reform and Transformation, Heriot Watt University.
    14. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    15. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    16. Edem Maxwell Azila-Gbettor & Eli Ayawo Atatsi & Faith Deynu, 2015. "An Exploratory Study of Effects of Prepaid Metering and Energy Related Behaviour among Ghanaian Household," International Journal of Sustainable Energy and Environmental Research, Conscientia Beam, vol. 4(1), pages 8-21.
    17. Meles, Tensay Hadush, 2020. "Impact of power outages on households in developing countries: Evidence from Ethiopia," Energy Economics, Elsevier, vol. 91(C).
    18. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LP, vol. 7(4), pages 465-506, December.
    19. Jacome, Veronica & Ray, Isha, 2018. "The prepaid electric meter: Rights, relationships and reification in Unguja, Tanzania," World Development, Elsevier, vol. 105(C), pages 262-272.
    20. repec:wly:soecon:v:82:2:y:2015:p:361-384 is not listed on IDEAS
    21. Fobi, Simone & Deshpande, Varun & Ondiek, Samson & Modi, Vijay & Taneja, Jay, 2018. "A longitudinal study of electricity consumption growth in Kenya," Energy Policy, Elsevier, vol. 123(C), pages 569-578.
    22. Giovanni Cerulli, 2022. "Econometric Evaluation of Socio-Economic Programs," Advanced Studies in Theoretical and Applied Econometrics, Springer, edition 2, number 978-3-662-65945-8, July-Dece.
    23. Shaun McRae, 2015. "Infrastructure Quality and the Subsidy Trap," American Economic Review, American Economic Association, vol. 105(1), pages 35-66, January.
    24. Kelsey Jack & Grant Smith, 2020. "Charging Ahead: Prepaid Metering, Electricity Use, and Utility Revenue," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 134-168, April.
    25. Yueming Qiu & Bo Xing & Yi David Wang, 2017. "Prepaid Electricity Plan And Electricity Consumption Behavior," Contemporary Economic Policy, Western Economic Association International, vol. 35(1), pages 125-142, January.
    26. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, . "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693, September.
    27. Gouthami Padam & Dana Rysankova & Elisa Portale & Bryan Bonsuk Koo & Sandra Keller & Gina Fleurantin, 2018. "Ethiopia – Beyond Connections," World Bank Publications - Reports 30102, The World Bank Group.
    28. Shane Frederick & George Loewenstein & Ted O'Donoghue, 2002. "Time Discounting and Time Preference: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 40(2), pages 351-401, June.
    29. Brounen, Dirk & Kok, Nils & Quigley, John M., 2013. "Energy literacy, awareness, and conservation behavior of residential households," Energy Economics, Elsevier, vol. 38(C), pages 42-50.
    30. Oseni, Musiliu O., 2015. "Assessing the consumers’ willingness to adopt a prepayment metering system in Nigeria," Energy Policy, Elsevier, vol. 86(C), pages 154-165.
    31. Juergen Jung & Jialu Liu Streeter, 2015. "Does health insurance decrease health expenditure risk in developing countries? The case of China," Southern Economic Journal, John Wiley & Sons, vol. 82(2), pages 361-384, October.
    32. Njabulo Kambule & Kowiyou Yessoufou & Nnamdi Nwulu & Charles Mbohwa, 2019. "Temporal analysis of electricity consumption for prepaid metered low- and high-income households in Soweto, South Africa," African Journal of Science, Technology, Innovation and Development, Taylor & Francis Journals, vol. 11(3), pages 375-382, April.
    33. Giovanni Cerulli, 2014. "ivtreatreg: A command for fitting binary treatment models with heterogeneous response to treatment and unobservable selection," Stata Journal, StataCorp LP, vol. 14(3), pages 453-480, September.
    34. Telles Esteves, Gheisa Roberta & Cyrino Oliveira, Fernando Luiz & Antunes, Carlos Henggeler & Souza, Reinaldo Castro, 2016. "An overview of electricity prepayment experiences and the Brazilian new regulatory framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 704-722.
    35. Sascha O. Becker & Andrea Ichino, 2002. "Estimation of average treatment effects based on propensity scores," Stata Journal, StataCorp LP, vol. 2(4), pages 358-377, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Klug, Thomas W. & Beyene, Abebe D. & Meles, Tensay H. & Toman, Michael A. & Hassen, Sied & Hou, Michael & Klooss, Benjamin & Mekonnen, Alemu & Jeuland, Marc, 2022. "A review of impacts of electricity tariff reform in Africa," Energy Policy, Elsevier, vol. 170(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 265675, Collaborative Masters Program in Agricultural and Applied Economics.
    2. Sodokin, Koffi & Djafon, Joseph Kokouvi & Dandonougbo, Yevessé & Akakpo, Afi & Couchoro, Mawuli K. & Agbodji, Akoété Ega, 2023. "Technological change, completeness of financing microstructures, and impact on well-being and income inequality," Telecommunications Policy, Elsevier, vol. 47(6).
    3. Wong, Jason Chun Yu & Blankenship, Brian & Urpelainen, Johannes & Balani, Kanika & Ganesan, Karthik & Bharadwaj, Kapardhi, 2022. "Understanding electricity billing preferences in rural and urban India: Evidence from a conjoint experiment," Energy Economics, Elsevier, vol. 106(C).
    4. Origo, Federica, 2009. "Flexible pay, firm performance and the role of unions. New evidence from Italy," Labour Economics, Elsevier, vol. 16(1), pages 64-78, January.
    5. Crinò, Rosario, 2012. "Imported inputs and skill upgrading," Labour Economics, Elsevier, vol. 19(6), pages 957-969.
    6. Erhardt, Eva Christine, 2017. "Microfinance beyond self-employment: Evidence for firms in Bulgaria," Labour Economics, Elsevier, vol. 47(C), pages 75-95.
    7. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 276460, Collaborative Masters Program in Agricultural and Applied Economics.
    8. Klug, Thomas W. & Beyene, Abebe D. & Meles, Tensay H. & Toman, Michael A. & Hassen, Sied & Hou, Michael & Klooss, Benjamin & Mekonnen, Alemu & Jeuland, Marc, 2022. "A review of impacts of electricity tariff reform in Africa," Energy Policy, Elsevier, vol. 170(C).
    9. Paolo Naticchioni & Silvia Loriga, 2011. "Short and Long Term Evaluations of Public Employment Services in Italy," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 57(3), pages 201-229.
    10. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    11. Dragana Radicic & Geoffrey Pugh & David Douglas, 2020. "Promoting cooperation in innovation ecosystems: evidence from European traditional manufacturing SMEs," Small Business Economics, Springer, vol. 54(1), pages 257-283, January.
    12. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    13. Candon, David, 2018. "The effect of cancer on the labor supply of employed men over the age of 65," Economics & Human Biology, Elsevier, vol. 31(C), pages 184-199.
    14. Burger, Anže & Hogan, Teresa & Kotnik, Patricia & Rao, Sandeep & Sakinç, Mustafa Erdem, 2023. "Does acquisition lead to the growth of high-tech scale-ups? Evidence from Europe," Research in International Business and Finance, Elsevier, vol. 64(C).
    15. Ashok K. Mishra & Anjani Kumar & Pramod K. Joshi & Alwin D'Souza, 2018. "Cooperatives, contract farming, and farm size: The case of tomato producers in Nepal," Agribusiness, John Wiley & Sons, Ltd., vol. 34(4), pages 865-886, October.
    16. D. Mark Anderson, 2013. "The Impact Of Hiv Education On Behavior Among Youths: A Propensity Score Matching Approach," Contemporary Economic Policy, Western Economic Association International, vol. 31(3), pages 503-527, July.
    17. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    18. Paudel, G. & Krishna, V. & McDonald, A., 2018. "Why some inferior technologies succeed? Examining the diffusion and impacts of rotavator tillage in Nepal Terai," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277149, International Association of Agricultural Economists.
    19. Corbacho, Ana & Philipp, Julia & Ruiz-Vega, Mauricio, 2015. "Crime and Erosion of Trust: Evidence for Latin America," World Development, Elsevier, vol. 70(C), pages 400-415.
    20. Owusu, Victor & Abdulai, Awudu & Abdul-Rahman, Seini, 2011. "Non-farm work and food security among farm households in Northern Ghana," Food Policy, Elsevier, vol. 36(2), pages 108-118, April.

    More about this item

    Keywords

    Electricity utility; Energy access; Propensity score matching; Instrumental variables; Satisfaction;
    All these keywords.

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:170:y:2022:i:c:s0301421522004700. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.