Impact of Trade Integration between Tunisia and the European Union on Foreign Direct Investments
Bibliographic record
Abstract
This study investigates the impact of Tunisia’s economic integration particularly through the Free Trade Agreement (FTA) with the European Union (EU) on foreign direct investment (FDI) inflows into the country. The analysis adopts a multidimensional theoretical framework, focusing on key structural determinants of FDI attractiveness such as trade openness, human capital, infrastructure quality, political stability, and macroeconomic conditions. A mixed-method approach is employed, combining a systematic literature review with a two-step econometric modeling strategy. Robust causal inference techniques such as instrumental variables and propensity score matching are used to address potential specification biases and improve the reliability of the findings. The results show that the Tunisia-EU Association Agreement has a positive and statistically significant effect on FDI inflows, increasing them by approximately 12% over the period studied. This finding highlights the role of even sector-specific trade integration (limited to industrial goods) in boosting external capital. This research contributes to the literature on trade agreements by offering robust empirical evidence and provides actionable insights for policymakers regarding trade policy and industrial development strategies in developing economies.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".