Empirical Analysis of the Effect of Accountability on Budget Implementation in Ondo State Nigeria
Bibliographic record
Abstract
The paper aimed at analyzing the effect of accountability on budget implementation in Nigeria using Ondo State Ministry of Finance as a case study. The paper adopts a survey design and secondary data which were obtained from statistical bulletin of Ministry of Finance. The time series data covers the period of eight (8) years from 2007-2014. The data was analyzed using ordinary least square (OLS) and Augmented Dickey Fuller (ADF) unit root test with the aid of E-view 7 Software Statistical package. The findings reveal that the coefficient of multiple determination is low in explaining the annual approved budget estimates, besides, the formulated model does not show a good fit of the total approved budget estimates due to some unforeseen occurrences that affects the measure of accountability during budget implementation. This was further justified by the t-test and F-test results. The paper recommended the use of accurate data which will be predicated on the performance of past budgets. Also, there is a need for strict observance of budget discipline by the executive to guide against extra-budgetary spending.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".