A macro econometric model for forecasting the hotel-room night demand ::the case of Switzerland
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article proposes a macroeconomic-oriented method to forecast hotel room demand in Switzerland for the period stretching from the third quarter of 1974 to the fourth quarter of 2013. The method increases accuracy by weighting characteristics of the inbound tourists’ economies for their relative contribution. It adopts the VECM technique, which produces reliable forecasts in both the short and long run without making ex ante assumptions regarding the causality of the explanatory variables. The results indicate that the method outperforms alternative forecasting methods in both the short and long run. The analysis shows that in the short run hotel room demand depends on income in visiting countries but not on the real GDP of Switzerland while in the long run demand depends on the real exchange rate and the real GDP of Switzerland.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it