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Record W2621295890 · doi:10.1111/obes.12175

Is the Quarter of Birth Endogenous? New Evidence from Taiwan, the US, and Indonesia

2017· article· en· W2621295890 on OpenAlex
Elliott Fan, Jin‐Tan Liu, Yen‐Chien Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOxford Bulletin of Economics and Statistics · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Labor, and Family Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Instrumental variableDemographyOddsEarningsCensusPopulationSample (material)Demographic economicsEconomicsGeographyMedicineLogistic regressionEconometricsSociology

Abstract

fetched live from OpenAlex

Abstract Recent evidence based on US data suggests that the quarter or month of birth (QOB or MOB) may be endogenous, since family characteristics can explain up to 50% of the effects of QOB on the education outcomes and earnings of adult males. In this study, based on a sample of one million Taiwanese siblings, we examine university admission at age 18 as our outcome variable and find that at school entry, the oldest (September born) children are 31–38% more likely to be admitted into university at age 18 than the youngest (August born) children, indicating strong seasonality in university admission. The inclusion of controls for family background is found to explain only a small portion of these effects, particularly for males. Given that such results are at odds with the recent US evidence, we revisit the US Census data and find that when racial differences are properly controlled for in the estimation, even a rich set of family characteristics is capable of explaining only a minor proportion of the QOB effects. Furthermore, using data from the US and Indonesia, we find that seasonal temperature variation is unlikely to be an important contributor to the US‐Taiwan disparity. Our findings imply that the validity of using QOB or MOB as an instrumental variable may be dependent on the population being studied and the sample selected.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.358
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.259
Teacher spread0.221 · 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