Impact of Foreign Direct Investment on Economic Growth — Case Study of the SEE Countries
Bibliographic record
Abstract
The main focus of this study is on foreign direct investment (FDI), which (through its direct and indirect contributions) can serve as the main driver of economic development for countries in general.The study examines countries in Southeastern Europe (SEE) -Kosovo, Albania, Montenegro, Serbia, Northern Macedonia and Bosnia and Herzegovina for the period 2005-2020 for the dependent variable, i.e., GDP, and for the independent variables: Goods and Services, Wages, Social Transfers, Subsidies, Investment Expenditures, and FDI.The techniques used to analyse the data include the descriptive method, the regression model, the DW test and (for multicollinearity between variables) the VIF test.In general, the study finds a positive and significant relationship between economic growth and FDI flows in some countries, but not in Kosovo and Bosnia and Herzegovina.Based on the results studied, more appropriate FDI policies are suggested.It is suggested that policy makers in these countries not only respond to protect the deterioration of GDP, but also support the infrastructure for doing business.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".