Investigating the business cycle properties of tourist flows to Barbados
Bibliographic record
Abstract
This paper evaluates whether the tourism cycles of Barbados can be regarded as a direct consequence of business cycles of the UK, US, Canada and Barbados. The cyclical components of the series are extracted using the structural time series framework by Harvey, 1989, and the interrelations between the variables are evaluated using innovation accounting. The variance decompositions suggests that shocks to the source country business cycle series can explain up to 25 percent of the future variation of the Barbadian tourism cycle. Shocks to the Barbadian business cycle only seem to significantly affect the Canadian tourist cycle. This implies that for tourist arrivals from the US and UK are more influenced by economic developments in their respective home countries, rather than those of Barbados. Finally, Granger-causality tests indicate that past values of the source country business cycles can help better predict present values tourist arrivals to Barbados, while past values of the Barbadian cycle only Granger-cause the Canadian tourist cycle. An interesting observation is that there appears to be some delay in the reaction of the tourism cycle to the business cycles. Thus, policy makers should take advantage of the delay between the two cycles, and adopt some form of countercyclical policy to soften the impact of negative income shocks in the UK, US or Canada on the Barbadian economy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".