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Record W3123537006

Dwindling U.S. internal migration: Evidence of spatial equilibrium or structural shifts in local labor markets?

2010· preprint· en· W3123537006 on OpenAlexaff
Mark D. Partridge, Dan S. Rickman, M. Rose Olfert, Kamar Ali

Bibliographic record

VenueRePEc: Research Papers in Economics · 2010
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of LethbridgeUniversity of Saskatchewan
Fundersnot available
KeywordsEconomicsAmenityUrban hierarchyRedistribution (election)Empirical evidencePopulationQuantile regressionInternal migrationHierarchyEconomic geographyUrbanizationGeneral equilibrium theoryDemographic economicsLabour economicsEconometricsMacroeconomicsMarket economyEconomic growthDeveloping country
DOInot available

Abstract

fetched live from OpenAlex

This paper examines whether the significant downward shift in U.S. gross migration rates after 2000 is indicative of the economy nearing a stationary spatial equilibrium. Nearness to spatial equilibrium would imply that site-specific factors such as amenities and location within the urban hierarchy have little influence on migration because their values have been capitalized into prices, causing interregional utility levels to become approximately equal. Yet, in an examination of U.S. counties, we find empirical evidence of only a mild ebbing of natural amenity-based migration after 2000 and little slowing of population redistribution from peripheral towards core urban areas. Instead, the primary finding is a downward shift in the responsiveness of population to spatially asymmetric demand shocks post-2000, and associated increased responsiveness of local area labor supply, more consistent with European regional labor markets. Quantile regression analysis suggests that this shift does not relate to a difference in regional labor market tightness across the two decades

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.048
GPT teacher head0.306
Teacher spread0.258 · 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 designObservational
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

Citations0
Published2010
Admission routes1
Has abstractyes

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