2007), “A No-Arbitrage Analysis of Macroeconomic Determinants of Term Structures and the Exchange Rate,” Working Paper
Bibliographic record
Abstract
Bank of Canada working papers are theoretical or empirical works-in-progress on subjects in economics and finance. The views expressed in this paper are those of the authors. No responsibility for them should be attributed to the Bank of Canada. ISSN 1701-9397 © 2007 Bank of Canada ii We study the joint dynamics of macroeconomic variables, bond yields, and the exchange rate in an empirical two-country New-Keynesian model complemented with a no-arbitrage term structure model. With Canadian and US data, we are able to study the impact of macroeconomic shocks from both countries on their yield curves and the exchange rate. The variance decomposition of the yield level shows that the US monetary policy and aggregate supply shocks explain a majority of the unconditional variations in Canadian yields. They also explain up to 50% of the variations in the expected excess holding period returns of Canadian bonds. In addition, Canadian monetary policy shocks explain more than 70 % of the variations in Canadian yields over short and medium forecast horizons. It also explains around 40 % of the expected excess holding period returns of Canadian bonds. Both Canadian and US macroeconomic shocks help explain the dynamics of the exchange rate and the time-varying exchange risk premium.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".