Explaining Tourism Inflows in Greece: A Macroeconometric Approach
Bibliographic record
Abstract
This paper investigates the determinants of tourism inflows to Greece. The significance of the specific sector for the Greek economy varies from 15% to 20% of GDP (measured directly or indirectly respectively). Building on the existing literature, panel data estimation techniques are used, with explanatory variables including selected macroeconomic indicators and (relative) price indices. The main innovation of the paper is that, regarding the cross section dimension of the sample, disaggregated data based on the country (or area) of origin are used, combined with the corresponding macroeconomic aggregates. The time-span of the data is the 2004-2010 period, with the specific econometric techniques used taking into account both the statistical properties of variables and the differences between the various cross sections. The main conclusion of the paper is that the macroeconometric approach to explaining tourist arrivals provides a very satisfactory model fit, with explanatory variables explaining a significant part of the variability of the dependent variable.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".