Essays on the Economics of Immigration
Notice bibliographique
Résumé
My dissertation consists of three papers studying the impact of social networks and employment mobility on Canadian immigrants, and the effects of economic conditions and immigration policy changes on international Ph.D. students in Canada. In the first paper, I use the Longitudinal Survey of Immigrants to Canada (LSIC) to examine the effects of social networks on labour market outcomes of newly arrived Canadian immigrants. I find that the presence of initial networks at landing significantly increases the probability of getting a network job and reduces the probability of getting a formal job after landing. Across immigration categories, network effects vary, with the largest effect among the Refugees, followed by the Family Class, and then the Economic Class immigrants. In each class, low-educated immigrants rely more on networks to find a job than high-educated ones. By separating close ties into kinship and friendship, I find that family has stronger effects on employment outcomes. Moreover, the development of the network is important over time. Economic immigrants gain from more diverse networks, while the Refugees improve their employment outcomes by frequently contacting their networks. Finally, social networks play a limited role in determining the quality of immigrants' first jobs. The second paper examines employment mobility and its effects on long-run earnings inequality among Canadian male immigrants using the Longitudinal Immigration Database (IMDB) and linked tax data. Incorporating employment risk and earnings mobility, I find long-run earnings inequality among male immigrants is up to 34 percent lower than the current inequality (a 90/10 ratio of 4.92 versus 7.51). Further, I find that around 70 to 80 percent of the total long-run inequality reduction happens within the first 5 years with the remainder occurring by 15 years. Among immigration categories, the Refugees experience the highest level of both earnings mobility and employment risk, while employment mobility mainly happens at the bottom of the earnings distribution for the Family Class and Economic Class. These findings indicate high current earnings inequality among the immigrant population is not persistent in the long run. This is good news. One concerning factor is that the employment risk is concentrated at the bottom of the earnings distribution, especially for the Refugees. In the third paper, I study the effect of changing economic conditions and immigration policies on international Ph.D. students in Canada. After arriving in a host country, they are prone to economic conditions like domestic students and are also likely to be affected by immigration policies. Using the IMDB, I find that, unlike domestic students, international doctoral students experience a shorter study duration under adverse economic conditions. At the same time, a higher unemployment rate negatively affects international Ph.D. students as it associates with a lower probability of both getting permanent resident (PR) status during the study and remaining in Canada in the following year after finishing their studies. Immigration policies are also found to significantly correlate with the students' outcomes. When PR policies are less restrictive, international students have shorter study durations and are more likely to get PR while studying and stay in Canada after studying. Although there is no evidence that relaxed work permit policies affect the study duration of international Ph.D. students, they are shown to negatively correlate with their probability of getting PR during the study period and to substantially improve the retention likelihood.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».