Demographic transition, demographic dividendand economic growth in Nigeria
Bibliographic record
Abstract
Changes in age structure that results from demographic transition have economic consequences. This paper identifies the period of potential window of opportunity or demographic dividends created by Nigeria’s demographic transition. This is done by simulating the period of the demographic window of opportunity in Nigeria. In a simulation covering 1950 – 2050 our results reveal that Nigeria entered the window of opportunity in 2003 and will last beyond year 2050. The highest benefit will accrue in years 2032 and 2033 when the dividend can account for more than 10% of the growth of GDP per capita even if the current performance scenario continues to exist. However, the paper notes that the demographic dividend is not automatically realized and Nigeria needs to embark on strategies that will develop her human capital and position her towards not only capturing the first dividend but the second dividend as well.Keywords: demographic transition; demographic dividends;national transfer accounts (NTA); economic lifecycle;economic support ratioRésumé Les changements dans la structure d'âge qui provient de la transition démographique ont des conséquences économiques. Ce papier identifie la période de fenêtre potentielle d'opportunité ou de dividendes démographiques créés par la transition démographique du Nigeria. C'est fait en simulant la période de la fenêtre démographique d'opportunité au Nigeria. Dans une simulation couvrant 1950 – 2050. Nos résultats révèlent que le Nigeria est entré dans la fenêtre d'opportunité en 2003 et durera au-delà de l'année 2050. Le plus haut avantage s'accumulera au cours des années 2032 et 2033 où le dividende peut représenter plus de 10 % de la croissance de PIB par habitant même si le scénario de performance actuel continue à exister. Pourtant, le papier note que le dividende démographique n'est pas automatiquement réalisé et le Nigeria doit entreprendre des stratégies qui développeront sa capitale humaine et la placeront vers le fait de non capturer seulement le premier dividende, mais le deuxième dividende aussi.Mots clé: la transition démographique, les dividendes démographiques, les comptes de transfert nationaux (NTA), life cyclé économique, le rapport de soutien économique
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".