Macroeconomic Determinants of Foreign Direct Investment in Sierra Leone: An Empirical Analysis
Bibliographic record
Abstract
This study presents an empirical investigation into the macroeconomic determinants of Foreign Direct Investment in Sierra Leone between 1990 and 2013 in both the long and the short run. The Ordinary Least Squares (OLS) estimation is used and the time series properties of the variables were examined in the process. It first tests for unit root using the Augmented Dickey Fuller (ADF) test. The Johansen co-integration technique was employed to derive the long-run relationship. The result shows that market size, openness, exchange rate and natural resource availability exert positive relationship with FDI while inflation and money supply exert a negative one. The short run error correction model was also employed and reveals that market size, economy openness, inflation and natural resource availability are the main determinants of FDI inflow to Sierra Leone. Policy recommendation calls for the expansion of the country’s GDP, government strengthening the implementation of its reform agenda, strengthening its monetary policy to curtail inflation, and to embark on more infrastructural development all of which have the potential to attract more FDI.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".