Environmental Impact of Foreign Direct Investment: The Role of Economic Complexity in Sub-Saharan Africa
Bibliographic record
Abstract
This study investigates the short-run and long-run effects of foreign direct investment (FDI), corruption, and economic complexity on the environment in twenty-five sub-Saharan African (SSA) countries from 1996 to 2018. Using a dynamic panel data model, the results provide broad support for the pollution haven hypothesis and the existence of the environmental Kuznets curve in SSA. Our results indicate that the economic complexity index (ECI) is associated with rising environmental degradation. Low-quality FDI weakens environmental standards, and corruption facilitates the shift of polluting industrial activities from advanced countries to developing countries with less strict environmental rules. The paper finds that corruption, low quality FDI, and higher ECI tend to exacerbate environmental degradation in SSA. By considering the ECI, this studies contributes to the literature, analyzing the relationship between these key variables and the environment for some of the most vulnerable African countries that are said to be greatly impacted by climate change.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".