Econometric Models of Student Loan Repayment in Canada
Bibliographic record
Abstract
Six months after a student ceases being enrolled full-time in an educational institution, a loan contracted with the Canada student loans program is said to be consolidated and its repayment is expected. Many ex-students will repay their loan in total (capital and interest) within a ten-year period. However, a non-negligible proportion of borrowers will experience difficulty in the repayment of their loans. We are able to shed a new light on these issues because we have access to unique data to estimate econometric models of the determinants of interest relief and claims (defaults) as well as duration models for the repayment of student loans. We found that finishing the program supported by a loan is essential to avoiding default. Therefore, it may be worth considering policies that will reward anyone who completes his or her program. On the other hand, too much flexibility in access to loans might encourage experiments by students that could turn disastrous for the student and the national loan program. A loan program should also come with some information on the risk involved for the student before he or she invests in a particular field or program. One particular concern is the relatively high level of default for students attending private schools. Relatively easy access to loans could be an invitation for private institutions to capitalize on that fact with various educational programs having little bearing on the reality of the labour market. Eventually serious institutions will establish a reputation, but for some students it will be too late. Another result concerns the interest relief measure that seems not to have played its role of helping the 1990-91 cohort of students to pass through difficult times. Six mois après avoir mis fin à leurs études, complétées avec succès ou non, les ex-étudiants sont tenus de rembourser leurs prêts d'études. Une majorité d'entre eux rembourseront la totalité de leurs prêts sur une période de 10 ans. D'autres connaîtront des difficultés à respecter leur engagement. Dans cette étude, nous profitons d'une base exceptionnelle de données individuelles sur les prêts d'études au Canada pour étudier les déterminants des remboursements ou non des prêts et la durée avant le remboursement complet. Les résultats économétriques montrent l'importance de terminer ses études dans les temps requis à la fois pour éviter de faire défaut et aussi pour accélérer la période de remboursement. Une politique à envisager serait de gommer une partie des prêts lorsque l'étudiant complète ses études dans les temps requis. L'autre résultat est que le programme du report des intérêts n'a pas semblé très efficace pour faciliter le remboursement des prêts d'études pour la cohorte 1990-91 étudiée. Finalement, un programme trop généreux de prêts d'études sans mise en garde sur les risques encourus par les étudiants d'investir dans certains programmes, notamment ceux opérés par le secteur privé, a des effets importants non seulement sur la pérennité du programme des prêts, mais aussi sur les mauvaises décisions de la part des étudiants dans leur choix d'études.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".