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Record W2969445039

Intergenerational income mobility in the UK : new evidence using the BHPS and understanding society

2019· preprint· en· W2969445039 on OpenAlexaboutno aff
Bertha Rohenkohl

Bibliographic record

VenueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York) · 2019
Typepreprint
Languageen
FieldSocial Sciences
TopicIntergenerational and Educational Inequality Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBritish Household Panel SurveyIncome elasticity of demandEconomicsIncome distributionEconometricsQuarter (Canadian coin)Demographic economicsSample (material)Net national incomeSocial mobilityPermanent income hypothesisHousehold incomeLabour economicsPublic economicsGeographyGross incomeMacroeconomicsMathematicsInequalitySociology
DOInot available

Abstract

fetched live from OpenAlex

Using a new dataset combining the British Household Panel Survey and Understanding Society, I estimate the intergenerational income elasticity in the UK for individuals born between 1973 and 1991. Employing the traditional OLS approach as well as an alternative two-stage residual method that better controls for life-cycle effects, my results indicate that the intergenerational income elasticity is approximately 0.25. This means that around one quarter of every additional 1% of income advantage enjoyed by parents is passed on to their children. I also estimate income rank coefficients, which are a measure of positional mobility in the income distribution and these results corroborate the analysis of elasticities. These main results are largely robust to changes in the specifications of the model, sample restrictions and to the use of different measures of income. I also obtain regional estimates of mobility, and find large differences between the North and South of England

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.426

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.353
GPT teacher head0.391
Teacher spread0.038 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2019
Admission routes1
Has abstractyes

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Same venueWhite Rose Research Online (University of Leeds, The University of Sheffield, University of York)Same topicIntergenerational and Educational Inequality StudiesFrench-language works237,207