Effect of Macroeconomic Variables on the FDI inflows: The Moderating Role of Political Stability: An Evidence from Pakistan
Bibliographic record
Abstract
This study has examined the moderating role of Political Stability (PS) on the relationships between macroeconomic variables and the Foreign Direct Investment (FDI) inflows in Pakistan. For that purpose, this study used the authentic annual data for the period 1991 to 2011. The empirical analysis involved using the ADF test to check the stationary of the data, the EViews software and hierarchal regression using SPSS 19.0 statistical software package. The results of the study confirmed that that GDP growth rate, exports, imports and balance of payment have positive significant effects on FDI inflows in Pakistan. On the other hand, the inflation rate was not significant in determining the FDI inflows in the country. However, the GDP growth rate and Balance of Payment tends to be a significant determinant of FDI inflows when the moderating effect of the Political stability is accounted for. Based on the findings of this study, it is strongly suggested that political stability is crucial for the country’s domestic and foreign investment expansion in the future course of direction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".