An Input-Output augmented Kaya Identity and Application: Quantile regression approach
Carbon emission from Africa’s tropical land in 2016 is 6 billion tonnes. Thus, Africa emits a substantial amount of carbon. It is therefore important to study the emission of carbon in Africa, taking Nigeria, the largest economy in Africa, as a case study. Currently, Nigeria experiences rapid increa...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-01-01
|
| Series: | Social Sciences and Humanities Open |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590291121001108 |
| _version_ | 1818701354165600256 |
|---|---|
| author | David Iheke Okorie |
| author_facet | David Iheke Okorie |
| author_sort | David Iheke Okorie |
| collection | DOAJ |
| description | Carbon emission from Africa’s tropical land in 2016 is 6 billion tonnes. Thus, Africa emits a substantial amount of carbon. It is therefore important to study the emission of carbon in Africa, taking Nigeria, the largest economy in Africa, as a case study. Currently, Nigeria experiences rapid increases in the level of carbon emissions. Production activities play key roles in understanding the level of carbon emission in an economy. Therefore, this article analyzes the drivers of carbon emission, from production activities, at different quantile levels. Hence, the proposed Augmented Kaya Identity (AKI) model incorporate the role of the input-output relationship in carbon emission from production activities. Generally, the results confirm that the choice of input-output relationship is a key determinant of carbon emission. The Nigerian carbon emission decreases in quantile and while some factors’ elasticities are constant, others are quantile-drive. The proposed model also outperforms the basic Kaya Identity aside from estimating the input-output relationship impact on carbon emission at all quantile levels. These findings are externally valid for other African countries. Among others, the policy implication of this article includes providing the evidence and justification for Africa to move to cleaner energy sources in production activities to reduce emissions. Also, it provides the tool & background evidence of the key drivers of carbon emission and their elasticities for policy formulation and implementation in African economies. |
| first_indexed | 2024-12-17T15:19:30Z |
| format | Article |
| id | doaj.art-5a36571405604d6b85fe642edc35a83d |
| institution | Directory Open Access Journal |
| issn | 2590-2911 |
| language | English |
| last_indexed | 2024-12-17T15:19:30Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Social Sciences and Humanities Open |
| spelling | doaj.art-5a36571405604d6b85fe642edc35a83d2022-12-21T21:43:26ZengElsevierSocial Sciences and Humanities Open2590-29112021-01-0141100214An Input-Output augmented Kaya Identity and Application: Quantile regression approachDavid Iheke Okorie0China Institute for Studies in Energy Policy (CISEP), School of Management, Xiamen University, 422 South Siming Road, Xiamen, 361005, ChinaCarbon emission from Africa’s tropical land in 2016 is 6 billion tonnes. Thus, Africa emits a substantial amount of carbon. It is therefore important to study the emission of carbon in Africa, taking Nigeria, the largest economy in Africa, as a case study. Currently, Nigeria experiences rapid increases in the level of carbon emissions. Production activities play key roles in understanding the level of carbon emission in an economy. Therefore, this article analyzes the drivers of carbon emission, from production activities, at different quantile levels. Hence, the proposed Augmented Kaya Identity (AKI) model incorporate the role of the input-output relationship in carbon emission from production activities. Generally, the results confirm that the choice of input-output relationship is a key determinant of carbon emission. The Nigerian carbon emission decreases in quantile and while some factors’ elasticities are constant, others are quantile-drive. The proposed model also outperforms the basic Kaya Identity aside from estimating the input-output relationship impact on carbon emission at all quantile levels. These findings are externally valid for other African countries. Among others, the policy implication of this article includes providing the evidence and justification for Africa to move to cleaner energy sources in production activities to reduce emissions. Also, it provides the tool & background evidence of the key drivers of carbon emission and their elasticities for policy formulation and implementation in African economies.http://www.sciencedirect.com/science/article/pii/S2590291121001108C22L70Q40Q54 |
| spellingShingle | David Iheke Okorie An Input-Output augmented Kaya Identity and Application: Quantile regression approach Social Sciences and Humanities Open C22 L70 Q40 Q54 |
| title | An Input-Output augmented Kaya Identity and Application: Quantile regression approach |
| title_full | An Input-Output augmented Kaya Identity and Application: Quantile regression approach |
| title_fullStr | An Input-Output augmented Kaya Identity and Application: Quantile regression approach |
| title_full_unstemmed | An Input-Output augmented Kaya Identity and Application: Quantile regression approach |
| title_short | An Input-Output augmented Kaya Identity and Application: Quantile regression approach |
| title_sort | input output augmented kaya identity and application quantile regression approach |
| topic | C22 L70 Q40 Q54 |
| url | http://www.sciencedirect.com/science/article/pii/S2590291121001108 |
| work_keys_str_mv | AT davidihekeokorie aninputoutputaugmentedkayaidentityandapplicationquantileregressionapproach AT davidihekeokorie inputoutputaugmentedkayaidentityandapplicationquantileregressionapproach |