Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures
| dc.contributor.advisor | Madhlopa, Amos | |
| dc.contributor.advisor | Tait, Louise | |
| dc.contributor.advisor | Moyo, Alfred | |
| dc.contributor.author | Mbewe, Samson | |
| dc.date.accessioned | 2019-02-05T13:01:22Z | |
| dc.date.available | 2019-02-05T13:01:22Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2019-02-01T11:15:06Z | |
| dc.description.abstract | The ability to access affordable, reliable and modern energy services presents a pathway to social and economic development. Yet, the lack of access to modern energy services is widespread in sub-Saharan Africa and developing Asia. Following the declaration to achieve universal access to energy by 2030 in the United Nation’s Millennium Development Goals and Sustainable Development Goals – several tools have emerged tracking and monitoring energy access and energy poverty. Earlier efforts have focused on measuring energy poverty from a unidimensional perspective while recent efforts have focused on a multidimensional measurement. However, the growing trend in tracking and monitoring energy poverty using multidimensional indicators has been applied limitedly in the context of South Africa. Part of this has been associated with the lack of detailed and reliable survey data. With access to detailed survey data, this study aimed to evaluate household energy poverty in South Africa by using both unidimensional and multidimensional measures. This study constructed the energy budget share, also known as Tenth-Percentile Rule (TPR) (unidimensional) and the multidimensional energy poverty index (MEPI) using data from wave 1 (2008) and wave 4 (2014-2015) of the National Income Dynamic Study (NIDS) of South Africa. A 10 percent threshold was used for the energy-budget share while a 0.3 cutoff point was used for the MEPI. This study first computed national-level estimates of household energy poverty, and subsequently decomposed these estimates by province, household income poverty status and household location (urban versus rural). A sensitivity analysis was performed to test for the stability in ranking of provinces when the energy poverty threshold of the TPR was varied from 7 to 13 percent, and the energy poverty cutoff k of the MEPI was changed from 0.2 to 0.4. The Spearman rank correlation coefficient was determined for each pair of ranking of provinces to establish the strength of correlation. Based on the TPR measure, results show that 21 and 13 percent of South African households lived in energy poverty in 2008 and 2014-2015, respectively. The MEPI measure indicates that 37 and 19 percent of the households lived in energy poverty in 2008 and 2014- 2015, respectively. Limpopo province had the highest rates of energy poverty in 2014-2015 with values of 25 percent (using TPR) and 52 percent (using MEPI). This study also found that by 2014-2015, only 23 percent (using the TPR) and 46 percent (using the MEPI) of energy poor households lived below the food poverty line of R430. Further, this study found that household energy poverty has reduced in rural areas and by 2014-2015, only 18 percent (using TPR) and 49 percent (using MEPI) of households located in rural areas lived in energy poverty. The lowest observed value of the Spearman rank correlation coefficient was 0.90. It is concluded that the overall household energy poverty has reduced in South Africa between 2008 and 2014-2015. The TPR gives lower estimates of energy poverty than the corresponding values obtained from the MEPI measure. There is negligible effect of varying the threshold values (within the studied range) of the TPR and k. | |
| dc.identifier.apacitation | Mbewe, S. (2018). <i>Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures</i>. (). University of Cape Town ,Engineering and the Built Environment ,Department of Mechanical Engineering. Retrieved from http://hdl.handle.net/11427/29336 | en_ZA |
| dc.identifier.chicagocitation | Mbewe, Samson. <i>"Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures."</i> ., University of Cape Town ,Engineering and the Built Environment ,Department of Mechanical Engineering, 2018. http://hdl.handle.net/11427/29336 | en_ZA |
| dc.identifier.citation | Mbewe, S. 2018. Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Mbewe, Samson AB - The ability to access affordable, reliable and modern energy services presents a pathway to social and economic development. Yet, the lack of access to modern energy services is widespread in sub-Saharan Africa and developing Asia. Following the declaration to achieve universal access to energy by 2030 in the United Nation’s Millennium Development Goals and Sustainable Development Goals – several tools have emerged tracking and monitoring energy access and energy poverty. Earlier efforts have focused on measuring energy poverty from a unidimensional perspective while recent efforts have focused on a multidimensional measurement. However, the growing trend in tracking and monitoring energy poverty using multidimensional indicators has been applied limitedly in the context of South Africa. Part of this has been associated with the lack of detailed and reliable survey data. With access to detailed survey data, this study aimed to evaluate household energy poverty in South Africa by using both unidimensional and multidimensional measures. This study constructed the energy budget share, also known as Tenth-Percentile Rule (TPR) (unidimensional) and the multidimensional energy poverty index (MEPI) using data from wave 1 (2008) and wave 4 (2014-2015) of the National Income Dynamic Study (NIDS) of South Africa. A 10 percent threshold was used for the energy-budget share while a 0.3 cutoff point was used for the MEPI. This study first computed national-level estimates of household energy poverty, and subsequently decomposed these estimates by province, household income poverty status and household location (urban versus rural). A sensitivity analysis was performed to test for the stability in ranking of provinces when the energy poverty threshold of the TPR was varied from 7 to 13 percent, and the energy poverty cutoff k of the MEPI was changed from 0.2 to 0.4. The Spearman rank correlation coefficient was determined for each pair of ranking of provinces to establish the strength of correlation. Based on the TPR measure, results show that 21 and 13 percent of South African households lived in energy poverty in 2008 and 2014-2015, respectively. The MEPI measure indicates that 37 and 19 percent of the households lived in energy poverty in 2008 and 2014- 2015, respectively. Limpopo province had the highest rates of energy poverty in 2014-2015 with values of 25 percent (using TPR) and 52 percent (using MEPI). This study also found that by 2014-2015, only 23 percent (using the TPR) and 46 percent (using the MEPI) of energy poor households lived below the food poverty line of R430. Further, this study found that household energy poverty has reduced in rural areas and by 2014-2015, only 18 percent (using TPR) and 49 percent (using MEPI) of households located in rural areas lived in energy poverty. The lowest observed value of the Spearman rank correlation coefficient was 0.90. It is concluded that the overall household energy poverty has reduced in South Africa between 2008 and 2014-2015. The TPR gives lower estimates of energy poverty than the corresponding values obtained from the MEPI measure. There is negligible effect of varying the threshold values (within the studied range) of the TPR and k. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures TI - Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures UR - http://hdl.handle.net/11427/29336 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/29336 | |
| dc.identifier.vancouvercitation | Mbewe S. Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures. []. University of Cape Town ,Engineering and the Built Environment ,Department of Mechanical Engineering, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29336 | en_ZA |
| dc.language.iso | eng | |
| dc.publisher.department | Department of Mechanical Engineering | |
| dc.publisher.faculty | Faculty of Engineering and the Built Environment | |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Energy and Development Studies | |
| dc.title | Investigating household energy poverty in South Africa by using unidimensional and multidimensional measures | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MPhil |