Impacts of Foreign Direct Investment on Economic Growth: Empirical Evidence from Australian Economy
Bibliographic record
Abstract
This paper examines foreign direct investment (FDI) inflows and its impact on economic growth in Australia. FDI inflows are considered to be a vital source of economic growth or development for any economy and it plays big role in growth in gross domestic product (GDP), improvement in infrastructure, employment creation, export and trade performance. This paper examines the relationship between FDI and economic growth of Australia through regression analysis between FDI and different measures of economic growth. The multiple regressions is used to derive conclusion on importance of FDI. The results highlight that FDI inflows contribute to the Australian economy including a growth in GDP, export performance and employment. Mining and quarrying has been identified as an attractive sector in which it has contributed to 7% of GDP, a large amount of capital has been invested and employed intensive labor. The result reflects absence of relationship between FDI and economic growth of Australia as two out three variables shows poor relationship with FDI. The findings provide critical information to Australian policy decision makers to make an informed decision with regard to attractive investment sectors and policies in encouraging foreign investors to invest in the country.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".