Financial Development, Governance and Economic Growth: A Causal Analysis
Bibliographic record
Abstract
This study seeks to establish the causal relationships among variables of financial sector development, governance quality, and economic growth in Liberia. To achieve this objective, the researchers gathered secondary time series data from the World Development Indicators and the Worldwide Governance Indicators covering the period 1980 to 2019. The Autoregressive Distributed Lag (ARDL) Model and the Granger Causality Test were used for estimations. The estimation results (particularly the Granger Causality Test) found a uni-directional causal relationship flowing from financial sector development to economic growth - implying that economic growth is caused by financial sector development. Among other things, this study recommends that policy measures that are meant to revamp the Liberian economy be channeled through the financial sector; and that the Government, through the Central Bank, ensures that lending interest rates on borrowed funds are kept in minimum range to enable the private sector acquire loanable funds for investment purposes.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".