Cointegration and Canada‐U.S. Term Structures: Does Accounting for Structural Breaks Make a Difference?
Bibliographic record
Abstract
Abstract Using weekly data on Canadian and U.S. T‐bill and T‐bond yields over the 1982 to 1996 period, we find evidence in support of the generalized interest parity model (i.e., co‐movement) for T‐bond term structures, but not for T‐bill term structures. This evidence is robust to the introduction of fractional cointegration. However, structural breaks induced by political uncertainty surrounding Quebec separation and Canada's move to zero inflation had larger impacts on the T‐bill term structure than on the T‐bond term structure. This paper highlights the importance of accounting for structural breaks, and how a failure to do so may affect statistical analyses undertaken by both financial economists and practitioners. As an example, we discuss the implications for portfolio management. In particular, incorrect conclusions that Canadian and U.S. T‐bill markets are not cointegrated can result in a less than optimal amount of diversification, thus affecting the performance of portfolio managers. Résumé En utilisant des données hebdomadaires de rendements sur les effets et bons du Trésor canadiens et américains pendant la période de 1982 à 1996, nos résultats sou‐tiennent le modéle géneralisé de la parité des taux d'in‐térěts (co‐mouvement) dans le cas des structures des échéances des bons du Trésor et non dans celui des effets du Trésor. Cette évidence est robuste à l'introduction de la co‐intégration fractionnelle. Cependant, les ruptures structurelles introduces par l'incertitude politique que présentent la séparation du Québec et les politiques anti‐inflationaires canadiennes ont eu un impact plus important sur les structures des échéances des effets que sur ceux des bons du Trésor, ce qui parvient à expliquer les refus de la théorie. La présente étude souligne l'importance de l'incorporation des ruptures structurelles sans laquelle les analyses statistiques entreprises par les économistes de finance et par les practiciens seraient inversement affectées. Entre autre, nous présentons les implications qu'ont les ruptures structurelles sur la ges‐tion de portefeuilles. En particulier, la conclusion incor‐recte que les marchés des effets du Trésor canadiens et américains ne sont pas sont cointégrés (lorsqu'ils le sont) mènerait à un niveau de diversification sous‐optimal, et donc, affecterait négativement la performance des gestionnaires de portefeuille.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".