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Record W7024732260

Should I Pay or Should I Go? Dutch Evidence on Tax-Induced Out-Migration

2023· report· en· W7024732260 on OpenAlexaff

Bibliographic record

VenueResearch Publications (Maastricht University) · 2023
Typereport
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsMontreal Council on Foreign Relations
Fundersnot available
KeywordsGovernment (linguistics)Work (physics)PaymentProduction (economics)
DOInot available

Abstract

fetched live from OpenAlex

We investigate the mobility response of workers to a loss in preferential tax treatment, exploiting a radical policy change that shortened the duration of the tax break available to high-skilled migrants to the Netherlands. The policy change only affected migrants who arrived from specific countries within a certain period. Using tax and population-wide data and a difference-in-differences approach, we uncover the causal effect of tax-induced emigration and show that taking away tax breaks from migrants strongly increases their likelihood of leaving. Crucially, our findings show that this effect is entirely driven by out-migration from the top 1% of the income distribution. No migration response was detected for those below the 95th earnings percentile. Individuals in the top 1% of the income distribution decrease their length of stay by 11.1% and are 18.3% less likely to remain beyond the end of the five years that they receive the tax break, while ‘highly mobile’ individuals also react in terms of both intensive and extensive duration margins when among top 5% of earners. We estimate that the elasticity of migration with respect to the net-of-tax rate for the<br/>top 1% of earners is 1.48 to 1.74. Regarding the distortionary effect of national policies on international tax competition, we show that the most mobile tax earners become much more likely to leave for a tax-friendly country post reform, and we conclude that, at least in terms of the change in taxable receipts from labor in the Netherlands, this policy was cost neutral.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.031
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.668
GPT teacher head0.499
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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