Projecting the fiscal impact of immigration in the European Union
Bibliographic record
Abstract
Abstract The increasing flow of immigrants into Europe over the last decade has generated a range of considerations in the policy agenda of many receiving countries. One of the main considerations for policymakers and public opinion alike is whether immigrants contribute their ‘fair’ share to their host country's tax and welfare system. In this paper, we assess the net fiscal impact of intra‐EU and extra‐EU migration in 27 European Union (EU) Member States. We find that migrants in the EU, on average, contribute more than natives to welfare states. However, when we take an age‐specific life‐cycle perspective, we find that natives generally show a higher net fiscal contribution than both groups of migrants. Among migrants, extra‐EU migrants contribute less than intra‐EU migrants. We then use a demographic microsimulation model to project the potential net fiscal impact of migration in the EU into the future. We show that despite the fact that intra‐EU migration contributes to reduce the strong negative impact of population ageing, its contribution is not sufficient to offset the negative fiscal consequences.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".