Determinants of Government Expenditure on Public Flagship Projects In Kenya
Bibliographic record
Abstract
The Kenya Vision 2030 flagship projects expected to generate rapid economic growth in the country are threatened by inadequate source of funding, financial management problems and failure to link policy, planning and expenditure budgeting. The projects continue to experience inadequacies in project appraisal and implementation time overruns. Therefore, without a clear financial framework, fiscal indiscipline, resource misallocation and inefficient use of resources will militate against achieving the Kenya Vision 2030 targets. The overall objective of this study was to evaluate determinants of government expenditure on public flagship projects in Kenya. The specific objectives were to: evaluate the influence of planning process; source of funds; and management responsibility on government expenditure on public flagship projects in Kenya. The theories reviewed in the study were public finance, budget, cost-benefit analysis and principal-agent which provided grounds for conceptual framework. The study employed descriptive research design, positivist philosophy and multiple regression model. The target population was the planned 348 flagship projects for the period 2008-2012. The unit of analysis was projects based on sample size of 96 stratified random sample while data was collected using a questionnaire. The findings showed that planning process, source of funds and management responsibility had significant positive influence in determining government expenditure on public flagship project in Kenya. The study recommended that, public entities should strengthen and improve planning process by deepening MTEF within programme-based budgeting; the National Treasury should increase resources required for financing public flagship projects by considering public-private-partnerships as a potential source; and public entities should improve, strengthen and enforce management responsibility when designing public flagship projects. The two areas suggested for further research were; impact of project characteristics on the choice of Public-Private Partnership financing model; and impact of fiscal decentralization on financing public projects in light of devolved systems of governance in Kenya.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".