Capital Account Liberalization and Growth in the WAMZ: An Empirical Analysis
Bibliographic record
Abstract
The paper employed recent time series econometrics to analyze and determine relationships between capital account liberalization and economic growth in the West African Monetary Zone2 (WAMZ) for the period 1980–2012. For the purpose of clearly ascertaining the impact of the variables of interest on economic growth, a country by country estimation was carried out. The short-run and long-run relationships between capital account openness and economic growth were investigated by applying the autoregressive distributive lag (ARDL) bounds testing approach suggested by Pesaran et al. (2001). The empirical results of the ARDL models showed a significant positive relationship between capital account liberalization and growth in Ghana and Sierra Leone. This suggests that the removal of restrictions on capital accounts in Ghana and Sierra Leone would promote economic growth in these countries in the long-run. Liberalization had positive and significant impact on growth in Ghana even in the short-run. However, there was no significant long-run relationship between liberalization and growth in The Gambia, Guinea, Liberia and Nigeria, implying that opening of the capital account should be gradual and complemented with sound macroeconomic and financial policy. Overall, the diagnostic tests indicated that our ARDL models were stable.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".