Empirical Study on Tourism and Economic Growth of Bahrain: An ARDL Bounds Testing Approach
Bibliographic record
Abstract
<p>This paper empirically investigates the tourism-led-growth hypothesis (TLGH) in case of Bahrain. Using time series econometrics techniques the study examines the long run relationship between international tourism and economic growth in Bahrain by using Autoregressive Distributed Lag (ARDL) model over the period of 1990 to 2014. The results obtained from the analyses show that there is a positive relationship between tourism development and economic growth in Bahrain. Moreover, the results indicate that there is unidirectional Granger causality flow from tourism to economic growth in Bahrain. Hence, the development of tourism activity will thus have a positive impact on Bahrain economy. Our findings imply that Bahrain may enhance its economic growth by strategically strengthening the tourism industry in the country. <br /><strong></strong></p>
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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) | 0.000 | 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".