MACROECONOMIC DETERMINANTS OF ECONOMIC GROWTH IN GHANA: COINTEGRATION APPROACH
Bibliographic record
Abstract
The study is on Macroeconomic Determinants of Economic Growth in Ghana using cointegration approach. The main objective of this study is to examine the major macroeconomic determinants of economic growth in Ghana between the periods 1970 and 2011 applying the Johansen method of cointegration. All the variables are integrated at first order, as a result the Johansen's cointegration approach was used. The study find out that physical capital and foreign aid had a positive effect on growth in real gross domestic product per capita. In the long run, physical capital, labour force, foreign direct investment, foreign aid, consumer price index, government expenditure and military rule are the significant determinants of growth in real gross domestic product per capita in Ghana. Also, in the short run, foreign direct investment and government expenditure are significant determinants of growth in real gross domestic product per capita. The result shows that there is unilateral directional causality between labour force and physical capital, physical capital and foreign direct investment, foreign aid and physical capital, physical capital and consumer price index, physical capital and military rule, labour force and foreign direct investment, consumer price index and labour force, foreign direct investment and foreign aid. Also, there is bidirectional causality between consumer price index and foreign direct investment. Base on the findings the following policy recommendations are made: Policies should be put in place to increase physical capital and foreign aid. Educational institutions should link up with the corporate organizations to train productive larbour force. Military rule had negative impact on growth in real GDP per capita, therefore, the Government must put in place strategies to protect and sustain democratic rule in Ghana.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".