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Record W2903565576 · doi:10.1257/pol.20160600

An Estimable Model of Income Redistribution in a Federation: Musgrave Meets Oates

2019· article· en· W2903565576 on OpenAlexaffabout
Kevin Milligan, Michael Smart

Bibliographic record

VenueAmerican Economic Journal Economic Policy · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsEconomicsDecentralizationRedistribution (election)Fiscal federalismPublic economicsUnitary stateExternalityIndirect taxFederalismPersonal income taxRedistribution of income and wealthState income taxTax reformDirect taxOptimal taxMacroeconomicsMicroeconomicsGross incomePublic goodPolitical scienceMarket economyLaw

Abstract

fetched live from OpenAlex

We develop a theory of cross-border income shifting in response to subnational personal taxation in a federation and examine its implications for the excess burden of personal taxes. We show how a properly chosen federal tax rate can offset the fiscal externality between states and facilitate decentralization, even in a heterogeneous federation where unitary taxation is suboptimal. Optimal taxes depend on the elasticities of national tax avoidance and of cross-state tax base shifting. We estimate these elasticities around a tax decentralization reform in Canada, finding both to be empirically relevant. We discuss the implications for optimal federalism. (JEL D31, H21, H23, H24, H26, H71, H77)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations13
Published2019
Admission routes2
Has abstractyes

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