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Essays in microeconomic theory

2021· other· en· W7037759937 sur OpenAlexaboutno aff

Notice bibliographique

RevueNottingham ePrints (University of Nottingham) · 2021
Typeother
Langueen
Domaine
Thématique
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLegislationEmpirical evidenceMechanism (biology)Game theoryCapital (architecture)Class (philosophy)Human settlementEmpirical research
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

This thesis uses game theory and microeconomics to investigate empirical puzzles. In Chapter 1 we provide a formal model to explain why new legislation that has widespread quickly in the last decades failed to achieve its objectives in accordance to recent evidence. In Chapter 2 we uncover a new class of equilibria in the canonical social learning setting with endogenous timing of decisions. We argue how our results can offer a social learning explanation for two applications: delays in the adoption of policy measures during the Covid-19 pandemic, and the timing of investments in the venture capital industry. In Chapter 3 we provide a formal model to explain recent evidence that correlates high levels of residential segregation based on income with low intergenerational mobility. \n \nApologies are considered as a cheap and strong mechanism to restore broken relationships. Between 1999 and 2011, the number of US states with apology laws, legislation that excludes the admissibility of apologies in court, increased from 2 to 38, along with all the Australian jurisdictions, the United Kingdom, most of the Canadian provinces, and Hong Kong. Legislators’ hope is that by passing these laws apologies will be encouraged, with the consequence that civil disputes will settle more often and lawsuits will be prevented. However, recent evidence from US shows that these laws have had the opposite effect: apology laws have increased the number of lawsuits. In Chapter 1 we provide an explanation for why apology laws fail that is consistent with the best available evidence. We show that apology laws may reduce settlements by encouraging insincere apologies which in turn induce plaintiffs not to accept apologies. We contribute to show on which type of relationships apology laws fail: apology laws preclude the settlement of cases that are socially valuable to be settled. Moreover, for the cases where these laws increase litigation we show that apology laws induce more miscarriages of justice and deter inter-party communication. \n \nIn Chapter 2 we ask: Does waiting to observe others’ action delay profitable choices? If so, for how long? We characterize long delays in a social learning environment. In contrast with previous work, we show the existence of equilibria in which agents end up adopting a profitable and risky policy with substantial delay. These results point to social learning as a plausible explanation for delays evidenced in the adoption of policy measures during the Covid-19 pandemic. Next, we allow agents to choose the quality of their information before deciding. We show how in this setting long delays may also exists, and how our equilibrium sheds light on the investment timing patterns evidenced in the venture capital industry. \n \nRecent evidence shows a negative association between social mobility and residential segregation based on income. In Chapter 3 we provide a theory that explains this link based on beliefs in a just world. Our argument is that segregated communities exhibit more polarized and pessimistic views that hard work pays off than integrated ones because families in those communities learn differently about the value of effort. This polarization and pessimism in segregated communities make in turn mobility lower, as those families with low beliefs in effort have higher income inertia. We model agents as trying to learn the relative importance of effort and predetermined factors in the generation of income. They learn from two sources, by socialization in neighbourhoods and from their dynastic income mobility experience. In a dynamic model, we characterize conditions on initial beliefs under which the society exhibits in the long run income segregation with low rates of social mobility, or income integration with high social mobility rates. We provide evidence for US that support our theoretical results. Using survey-data with beliefs in a just world we show that more segregated communities are correlated with more polarized and pessimistic views about the value for effort.

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)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,048

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0010,006
Communication savante0,0030,005
Science ouverte0,0010,001
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0140,002

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 Opus0,014
Tête enseignante GPT0,215
Écart entre enseignants0,201 · 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'étudeThéorique ou conceptuel
Domainenon disponible
GenreAutre

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

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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