FISCAL POLICY AND MIGRATION FLOWS: EVIDENCE FROM THE EUROPEAN UNION
Bibliographic record
Abstract
The focus of this paper is the impact of fiscal policies on international migration flows. The Tiebout hypothesis proposes that individuals consider differences in tax rates and social spending when making migration decisions. While evidence of the Tiebout hypothesis has been found in several domestic U.S. and Canadian studies, this is the first paper to test the Tiebout hypothesis using bilateral international migration flows. The Maastricht treaty has created a unique opportunity to study migration in an international context by removing legal barriers to migration within the European Union. Using data from EU countries throughout the 1980s and 1990s, this paper finds significant statistical support for the Tiebout hypothesis with regards to international migration flows. These results suggest that achieving greater fiscal harmonization across countries would lower migration flows. The results also imply that EU countries which are resistant to achieving fiscal harmonization with members may, as a result, have problems in attaining their other goal of reducing immigration (inward) from these countries.
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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 | 0.000 | 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".