The Tandem Movement of Natural Resource Price and the Price of the Loonie: An Empirical Analysis
Bibliographic record
Abstract
The views expressed in this paper are those of the author, and Statistics Canada is not responsible for them. Abstract: Canada is a net exporter of natural resources such as oil and gas and gold. In recent years, the movement between the natural resource prices and the exchange rate has been widely reported in the media. However, there is a lack of empirical analysis regarding this movement. This paper discusses the magnitude of this movement by linking a newly created natural resource price index and the exchange rate. Currently, Statistics Canada compiles annual data on production and sales revenues of a number of natural resources. Using these data from 1974 to 2006, a chained Fisher price index of natural resources is calculated. A regression model is used to examine the variation in the exchange rate due to the resource price growth along with other key variables. The augmented Dickey-Fuller test is conducted to examine the stationarity of these variables. The Johansen cointegation test demonstrates that there is a long run relationship between the exchange rate and the resource price index. Finally, the regression analysis reveals that the coefficient of the resource price index is statistically significant. 1
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".