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Enregistrement W4391593155 · doi:10.32920/25178636

Essays on Applied Microeconomics

2024· preprint· en· W4391593155 sur OpenAlexaff
Angélique Bernabé

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineSocial Sciences
ThématiqueMedia Influence and Politics
Établissements canadiensToronto Metropolitan UniversityYork UniversityUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésEarningsHonestyEconomicsStrategic complementsDominance (genetics)MicroeconomicsPsychologySocial psychologyBiology

Résumé

récupéré en direct d'OpenAlex

<p>My dissertation consists of three chapters in the area of applied microeconomics. The first chapter, written jointly with Tanjim Hossain and Haomiao Yu, investigates how strategic concerns and preferences for honesty affect people’s actions using two games.</p> <p>Two players simultaneously make reimbursement claims for the price of a damaged product, where reimbursements depend on players’ claims but not the actual price. In the game <em>Regular</em>, players’ best responses depend on their beliefs about others’ choices and both making the lowest claim is the unique equilibrium. The game <em>Upward</em> is dominance solvable and both making the highest claim the unique equilibrium.</p> <p>Yet, our experimental results show that players’ choices are significantly affected by the price in both games, with a larger impact in <em>Regular</em>. We need both strategic considerations and preferences for honesty to explain these findings. More players can be categorized as honest in <em>Regular</em> than in <em>Upward</em> and more as strategic in Upward than in Regular. Preferences for honesty lead to better coordination and increased earnings among players in <em>Regular</em>.</p> <p>The second chapter studies the impact of news coverage on women’s job mobility rates at the county level in the United States, exploiting the exogenous variation provided by the MeToo Movement. The average tone of news coverage at the county level is measured using novel data on sexual assault news coverage with natural language processing for categorizing the lexical choice of articles. The results show that the MeToo induced tone change of news coverage has a statistically significant impact on women’s propensity to switch jobs. In particular, increasing the tone change by one standard deviation decreases the job mobility rate of women by 12.8 percent.</p> <p>Additionally, the tone change of sexual assault news coverage does have a statistically significant impact on the labour market mobility of men in the sample with a different magnitude compared to women. There is no evidence that other news events, such as news on property crimes, have an impact on the job-to-job transition rates of women. The results suggest that the impact of sexual assault news coverage on women’s labour market decisions is amplified by the MeToo movement, especially when the information about sexual assaults is conveyed more positively compared to pre-MeToo Movement.</p> <p>The third chapter, written jointly with Boubacar Diop, Martino Pelli and Jeanne Tschopp, studies the long-run impacts of unexpected interruptions in regular schooling. Using storms as an exogenous shock, we examine how compulsory schooling disruptions affect educational attainments and the type of activity performed by individuals in young adulthood. We construct a unique continuous measure of childhood exposure to storms that varies by birth-year cohort and district for young adults in rural and urban India. We find that storms have substantial disruptive impacts on education. In the districts exposed to the most powerful winds, the estimates imply that children are 9% more likely to accumulate an educational delay and 6.5% less likely to obtain higher levels of education (beyond secondary school). In the long run, these delays have an impact on the type of labor market activity that these individuals perform. Using childhood exposure to storms as an instrument, we find that a one-year educational delay leads to a 42.6% drop in the probability of accessing regular salaried jobs. We determine that the impact of storms on education works through a permanent negative income shock.</p>

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,873
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,006

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 Opus0,039
Tête enseignante GPT0,342
Écart entre enseignants0,303 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
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

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

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