Assessing the Reliability of the 2005 CPI Basket Update in Canada Using the Bortkiewicz Decomposition* By
Bibliographic record
Abstract
Abstract: This paper uses the Bortkiewicz decomposition technique to analyze the relationship between price changes and shifts in consumer expenditures in Canada from 2001 to 2005. This technique has proved useful for analyzing the divergence between indexes and helps to asses the reliability of the 2005 Consumer Price Index basket update. In 2007, Statistics Canada moved from basket weights based on the 2001 Survey of Household Spending to a weighting pattern based on the 2005 Survey of Household Spending. Using the new updated 2005 basket of goods and services, the Paasche index for 2005 can be computed. Using this result, Bortkiewicz’s decomposition relating the Paasche and Laspeyres indexes can be studied. The Bortkiewicz analysis yielded expected results: the Paasche index was 1.68 % lower than the corresponding Laspeyres index for the “All-items ” classification. This indicates that, on the whole, from 2001 to 2005 consumers responded to rising prices by substituting away from relatively more expensive commodities and towards relatively cheaper ones. Computer equipment and supplies contributed more than any other basic class to the negative divergence between the Laspeyres and Paasche indexes. This negative impact, however, was partially offset by rent and mortgage interest cost, which were both leading positive contributors to the divergence between the two indexes. *The comments made by colleagues and, particularly, Andy Baldwin, George Beelen, Tarek Harchaoui, John Mallon, and Jennifer Withington are acknowledged with thanks.
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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 | 0.007 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".