Foreign Direct Investment and Economic Growth in Ghana
Bibliographic record
Abstract
The relationship between Foreign Direct Investment (FDI) and Economic Growth has been a topical issue for several decades. Policymakers in a large number of countries are engaged in creating all kinds of incentives to attract FDI, because it is assumed to positively affect economic growth. This paper investigates the effect of FDI on economic growth in Ghana. The paper, test for the presence of the long run linear relationship between FDI inflows and Economic Growth (GDP) for Ghana. The study employs various econometrics tools such as Dickey Fuller (DF) and Augmented Dickey Fuller (ADF) tests, Vector Auto Regression (VAR) and Johansen Co-integration test on time series data from the first quarter of 2001 to the fourth quarter of 2010. The results reveal that a long run relationship exists between the variables, and that FDI is positively related to economic growth in Ghana. Ghana should therefore continue to reform its economic and foreign policy to attract more investors which can help boost its economy. Keywords: Foreign Direct Investment, Economic Growth, Vector Auto Regression (VAR), Co- Integration, and Unit Roots
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".