Financial Development and Tax Revenue: How Catalytic Are Political Development and Corruption?
Bibliographic record
Abstract
Increasing domestic revenue mobilization remains a challenge for many governments, particularly in low-income countries. Using a sample of East African countries, the study sets off to investigate the impact of financial development from a multi-dimensional perspective on tax revenues for the period 1990 to 2014, and how political development and the control of corruption would enhance the observed nexus. The dynamic panel results from the system GMM estimation approach indicate a significant role of financial development overall and the financial institutions and financial markets in particular. A disaggregation of the duo suggests that it is the depth of financial institutions that greatly matters for tax revenue, with a one per cent change expected to yield about 0.26 per cent change in tax collections. It is then followed by their level of accessibility, financial market depth and efficiency. We fail to find significant evidence in support of financial market access and financial institutions efficiency although the possibility for the latter seems indismissible. Further evidence points to the catalytic nature of a good institutional and political environment in pursuit of higher tax-GDP ratio via financial development. Policies to promote the depth and accessibility of financial institutions as well the depth and efficiency of financial markets in East Africa alongside well-focused anti-corruption programs and democratic governance are likely to yield better fiscal outcomes in terms of domestic tax revenues critically needed to achieve the United Nations Sustainable Development Goals. We also confirm the positive role played by the lagged tax revenue, per capita GDP, trade openness, debt-to-GDP ratio and population density in the tax effort.
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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 | 0.000 | 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 | 0.000 |
| 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".