Is the 'Quarter of Birth' Endogenous? Evidence From One Million Siblings in Taiwan
Bibliographic record
Abstract
Recent studies based on US data have provided evidence to suggest that the 'quarter of birth' (QOB) may be endogenous and that the use of QOB as an instrumental variable will consequently produce inconsistent estimates (see Buckles and Hungerman, 2013).Such potential endogeneity is addressed in this study by estimating the effects of QOB on university attendance using a Taiwanese dataset on approximately one million siblings.Our estimations are mainly reliant upon the strength of the family fixed-effects model, a regression discontinuity design and a simulation procedure.Our results, in sharp contrast to the US findings, suggest that family background characteristics can explain very little of the relationship between QOB and the probability of university attendance at the age of 18.The disparity between the US and Taiwanese findings may be due to high-'socioeconomic status' (SES) women in the US disproportionately planning births away from the winter months, as suggested by Buckles and Hungerman (2013), whereas the seasonality of births is virtually identical for lowand high-SES mothers in Taiwan.Our findings imply that the endogeneity of QOB is of less concern in the case of Taiwan, perhaps due to the milder winter climate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".