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Enregistrement W3124477828 · doi:10.1257/jep.26.2.141

Why is the Teen Birth Rate in the United States So High and Why Does It Matter?

2012· preprint· en· W3124477828 sur OpenAlexaboutno aff
Melissa S. Kearney, Phillip B. Levine

Notice bibliographique

RevueThe Journal of Economic Perspectives · 2012
Typepreprint
Langueen
DomaineSocial Sciences
ThématiqueGender, Labor, and Family Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBirth rateDemographic economicsFace (sociological concept)EconomicsDemographyFertilitySociologyPopulation

Résumé

récupéré en direct d'OpenAlex

Teens in the United States are far more likely to give birth than in any other industrialized country in the world. U.S. teens are two and a half times as likely to give birth as compared to teens in Canada, around four times as likely as teens in Germany or Norway, and almost 10 times as likely as teens in Switzerland. Among more developed countries, Russia has the next highest teen birth rate after the United States, but an American teenage girl is still around 25 percent more likely to give birth than her counterpart in Russia. Moreover, these statistics incorporate the almost 40 percent fall in the teen birth rate that the United States has experienced over the past two decades. Differences across U.S. states are quite dramatic as well. A teenage girl in Mississippi is four times more likely to give birth than a teenage girl in New Hampshire--and 15 times more likely to give birth as a teen compared to a teenage girl in Switzerland. This paper has two overarching goals: understanding why the teen birth rate is so high in the United States and understanding why it matters. Thus, we begin by examining multiple sources of data to put current rates of teen childbearing into the perspective of cross-country comparisons and recent historical context. We examine teen birth rates alongside pregnancy, abortion, and "shotgun" marriage rates as well as the antecedent behaviors of sexual activity and contraceptive use. We seek insights as to why the rate of teen childbearing is so unusually high in the United States as a whole, and in some U.S. states in particular. We argue that explanations that economists have tended to study are unable to account for any sizable share of the variation in teen childbearing rates across place. We describe some recent empirical work demonstrating that variation in income inequality across U.S. states and developed countries can explain a sizable share of the geographic variation in teen childbearing. To the extent that income inequality is associated with a lack of economic opportunity and heightened social marginalization for those at the bottom of the distribution, this empirical finding is potentially consistent with the ideas that other social scientists have been promoting for decades but which have been largely untested with large data sets and standard econometric methods. Our reading of the totality of evidence leads us to conclude that being on a low economic trajectory in life leads many teenage girls to have children while they are young and unmarried and that poor outcomes seen later in life (relative to teens who do not have children) are simply the continuation of the original low economic trajectory. That is, teen childbearing is explained by the low economic trajectory but is not an additional cause of later difficulties in life. Surprisingly, teen birth itself does not appear to have much direct economic consequence. Moreover, no silver bullet such as expanding access to contraception or abstinence education will solve this particular social problem. Our view is that teen childbearing is so high in the United States because of underlying social and economic problems. It reflects a decision among a set of girls to "drop-out" of the economic mainstream; they choose non-marital motherhood at a young age instead of investing in their own economic progress because they feel they have little chance of advancement. This thesis suggests that to address teen childbearing in America will require addressing some difficult social problems: in particular, the perceived and actual lack of economic opportunity among those at the bottom of the economic ladder.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,047
Score d'incertitude au seuil0,094

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0010,002
Communication savante0,0030,002
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,280
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2012
Routes d'admission1
Résumé présentoui

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