Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/224737
Authors: 
Osuji, Emeka
Nwani, Stanley Emife
Year of Publication: 
2020
Citation: 
[Journal:] International Journal of Management, Economics and Social Sciences (IJMESS) [ISSN:] 2304-1366 [Volume:] 9 [Year:] 2020 [Issue:] 3 [Pages:] 131-160
Abstract: 
The purpose of this study was to examine the effectiveness of government expenditure framework in tracking social, economic, and environmental sustainable development goals (SDGs) in Nigeria. Using quarterly data (Q1:2000-Q4:2018), the study applied vector autoregression, variance decomposition, and impulse response estimation techniques. The estimates indicated a long-run association between government expenditure and SDGs indicators, with mixed impacts. In the short-run, government expenditure reduced poverty, while in the long-run it amplified poverty; government expenditure hurt SDG of rapid economic growth in the long-run, but promoted SDG of quality education in both short-run and long-run, through improvement in school enrolment. Furthermore, government spending amplified health-related SDGs in the long-run. Finally, government spending was found to adversely affect environmental sustainability through rising CO2 emission. From the empirical evidence, the study concluded that the public sector lacks the capacity to attain SDGs from environmental, growth, and poverty alleviation perspectives. The study contradicted the institutional and Wagner's theories but validated Hardin's tragedy of the commons. It proposes an effective public/private partnership, to improve spending outcomes, as the inevitable strategic action, if the attainment of the SDGs is to become a reality in Nigeria.
Subjects: 
Government expenditure
economic sustainability
social sustainability
environmental sustainability
vector autoregression
variance decomposition
JEL: 
H5
I1
P37
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/3.0/
Document Type: 
Article

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