The Impact of Financial Development, Foreign Direct Investment, and Trade Openness on Carbon Dioxide Emissions in Jordan: An ARDL and VECM Analysis Approach
Bibliographic record
Abstract
Jordan has made substantial strides in enhancing its economy by focusing on economic growth stimulants, which include financial development, foreign direct investment (FDI), and trade openness. However, these economic activities often lead to significant environmental risks. Despite their relevance, the existing literature has rarely examined the influence of these dynamics on environmental quality in the Middle East, particularly in Jordan. This study aims to investigate the influence of financial development, FDI, and trade openness on carbon dioxide (CO2) emissions in Jordan. To achieve this, the study employs the Autoregressive Distributed Lag (ARDL) technique and the Vector Error Correction Model (VECM) Granger causality approach, utilizing data sourced from the World Bank for the period from 1990 to 2022. The findings indicate that financial development, FDI, and trade openness positively impact CO2 emissions, thereby increasing environmental risks in both the short and long term. Additionally, there exists a bidirectional causal relationship between financial development and both FDI and trade openness, as well as between FDI and trade openness. It is imperative for Jordan to design strategies that balance economic growth with sustainable environmental practices.
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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 | 0.001 | 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".