Where do Energy-Poor Households Live? Empirical Evidence from Indonesia

Dewi Yuliandini Hasibuan(1), Rus'an Nasrudin(2),


(1) University of Indonesia
(2) University of Indonesia

Abstract

Empirical analysis on the links between geography and energy access in archipelago setting is still limited. In particular, the territorial identification of energy poverty in Indonesia is still missing. Our study maps geographical location and estimates factors that determines the probability of being energy poor household in relation to electricity. We used the OLS (Ordinary Least Square) estimation and utilized the socioeconomic survey (Susenas) combined with data on terrain elevation, presence of geographic features such as mountainside, topography characteristics, ocean and forest obtained from the village census (PODES). The results show that energy poverty in Eastern part of Indonesia is larger than in the Western. In Eastern Indonesia, we estimate that 13.5% of the total households are energy poor compared to the Western which only 7.21%. Households located in the forest area was the dominant factor to influence prevalence of energy poverty among geographic constraints, with magnitude of influence at 22-23 percentage point to non-forest residents. Secondly, the presence of steep-sloped terrain is the next meaningful geographical constraint with contribution effect to energy poverty prevalence at around 18 percentage point. The result highlighted priority of locations in which resource and policy to reduce energy deprivation need to be allocated.

Keywords

electricity infrastructure; energy poverty; energy geography; archipelagic country

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References

Barnes, D., Khandker, S., & Samad, H. (2011). Energy Poverty In Rural Bangladesh. Energy Policy. https://doi.org/10.1016/j.enpol.2010.11.014

Bohlmann, J., & Inglesi-Lotz, R. (2021). Examining The Determinants Of Electricity Demand By South African Households Per Income Level. Energy Policy. https://doi.org/10.1016/j.enpol.2020.111901

Burke, P., & Csereklyei, Z. (2016). Understanding The Energy-GDP Elasticity: A Sectoral Approach. Energy Economics. https://doi.org/10.1016/j.eneco.2016.07.004

Burke, P., & Kurniawati, S. (2018). Electricity Subsidy Reform In Indonesia: Demand-Side Effects On Electricity Use. Energy Policy. https://doi.org/10.1016/j.enpol.2018.02.018

Chaurey, A., Ranganathan, M., & Mohanty, P. (2004). Electricity Access For Geographically Disadvantaged Rural Communities-Technology And Policy Insights. Energy Policy, 32(15), 1693–1705. https://doi.org/10.1016/S0301-4215(03)00160-5

Dong, X., & Hao, Y. (2018). Would Income Inequality Affect Electricity Consumption? Evidence From China. Energy. https://doi.org/10.1016/j.energy.2017.10.027

Dornan, M. (2014). Access To Electricity In Small Island Developing States Of The Pacific: Issues And Challenges. Renewable And Sustainable Energy Reviews, 31, 726–735. https://doi.org/10.1016/j.rser.2013.12.037

Dugoua, E., Liu, R., & Urpelainen, J. (2017). Geographic And Socio-Economic Barriers To Rural Electrification: New Evidence From Indian Villages. Energy Policy, 106(10), 278–287. https://doi.org/10.1016/j.enpol.2017.03.048

Foster, V., Tre, J., Wodon, Q., & Bank, W. (2000). Energy Prices, Energy Efficiency, And Fuel Poverty. (Unpublished Paper) Workd Bank.

Goldemberg, J., Johansson, T., Reddy, A., & Williams, R. (1988). Energy For A Sustainable World. Energy For A Sustainable World. https://doi.org/10.1016/0301-4215(88)90170-x

Gregori, T., & Tiwari, A. (2020). Do Urbanization, Income, And Trade Affect Electricity Consumption Across Chinese Provinces? Energy Economics. https://doi.org/10.1016/j.eneco.2020.104800

Harrison, C. (2013). The Historical-Geographical Construction Of Power: Electricity In Eastern North Carolina. Local Environment. https://doi.org/10.1080/13549839.2012.748728

Hautdidier, B. (2015). The Comparative Tableau Of Mountains And Rivers: Emulation And Reappraisal Of A Popular 19th-Century Visualization Design. Environment And Planning A. https://doi.org/10.1177/0308518X15594901

Mendoza Jr, C., Cayonte, D., Leabres, M., Rose, L., & Manaligod, A. (2019). Understanding Multidimensional Energy Poverty In The Philippines. Energy Policy, 133(10), 110886. https://doi.org/10.1016/j.enpol.2019.110886

Karanfil, F., & Li, Y. (2015). Electricity Consumption And Economic Growth: Exploring Panel-Specific Differences. Energy Policy. https://doi.org/10.1016/j.enpol.2014.12.001

Nordhaus, W. (2006). Geography And Macroeconomics: New Data And New. findingsr10.1073/pnas.0509842103. PNAS.

Oum, S. (2019). Energy Poverty In The Lao PDR And Its Impacts On Education And Health. Energy Policy. https://doi.org/10.1016/j.enpol.2019.05.030

Pellini, E. (2021). Estimating Income And Price Elasticities Of Residential Electricity Demand With Autometrics. Energy Economics. https://doi.org/10.1016/j.eneco.2021.105411

Sambodo, M., & Novandra, R. (2019). The State Of Energy Poverty In Indonesia And Its Impact On Welfare. Energy Policy, 132(5), 113–121. https://doi.org/10.1016/j.enpol.2019.05.029

Sanchez, K., Foster, M., Nieuwenhuijsen, M., May, A., Ramani, T., Zietsman, J., & Khreis, H. (2020). Urban Policy Interventions To Reduce Traffic Emissions And Traffic-Related Air Pollution: Protocol For A Systematic Evidence Map. In Environment International. https://doi.org/10.1016/j.envint.2020.105826

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