Relative Cohort Size and Fertility in Latin America and the Caribbean: A Panel Data Approach
Bibliographic record
Abstract
Latin America has experienced a considerable decline in fertility over the past decades. The total fertility rate at region level was 4.57 in 1975 and fell to 2.29 in 2012. In this study, we examine effect of cohort size on fertility rate to test the applicability of the Easterlin hypotheses. According to the Easterlin hypotheses the income of young adults relative to the income of their parents is an important determinant of fertility. A major factor influencing relative income is relative cohort size. Persons born in large cohorts face greater difficulty in finding employment than persons born in small cohorts due to increased competition and consequently earn less, and, as a result have fewer children. We introduce relative cohort size into panel data models with the total fertility rate being estimated as a function of cohort size, the labor force participation rate of women, the infant mortality rate, the lagged total fertility rate, and the percent of the population that is urban. The results suggest that the Easterlin hypothesis holds in this region but the effect is weak. On the other hand, advanced medical technology hence decrease in infant mortality rate strongly affect fertility.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".