Government Expenditure and Economic Growth Nexus: Evidence from Nigeria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The need to better the lots of citizens through government expenditure has raised questions on the impact of government expenditure on the economic development and growth of nations. It is against this background that this paper examined the antecedent effect of government spending on the Nigerian economic growth. The general objective of the study is to ascertain the relationship between government expenditure and economic growth in Nigeria; specifically, the study examined: (i) the significance influence of government capital expenditure on economic growth in Nigeria and (ii) the significance influence of government recurrent expenditure on economic growth in Nigeria. The study employed ordinary least square (OLS) multiple regression analysis in estimating the specified model, with the Gross Domestic Product (GDP) as the dependent variable, while Capital Expenditure (CAPEXP) and Recurrent Expenditure (REXP) are the independent variables. Data between 1980 – 2013 were collected from secondary sources through the National Bureau of Statistics (NBS) and Central Bank of Nigeria (CBN). Results showed that in Nigeria, there exist a significant relationship between the government expenditure and economic growth. The study therefore recommends instilling fiscal discipline in government expenditures, and putting in place structural mechanisms to act as surveillance on capital spending so as to boost the nation’s human and social capital.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it