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Record W3036008237

The Price Effect of Trade: Evidence of the China Shock and Canadian Consumer Prices

2020· article· en· W3036008237 on OpenAlexaboutno aff
Myeongwan Kim

Bibliographic record

VenueCSLS Research Reports · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsConsumer price index (South Africa)Inflation (cosmology)Price indexChinaMonetary economicsRelative pricePersonal consumption expenditures price indexCommodityShock (circulatory)Wholesale price indexIndex (typography)Price levelInternational economicsAgricultural economicsMacroeconomicsConsumer confidence indexMonetary policyGeographyMarket economy
DOInot available

Abstract

fetched live from OpenAlex

The explosive growth in Chinese imports to Canada over the last two decades has had both negative and positive effects. In this paper, we look at the impact of Chinese imports on the prices Canadians pay for household consumption goods. We find Canadians have benefited from lower prices on some goods and lower inflation overall. To quantify the importance of Chinese imports for individual consumer products and map them to consumer price data, we construct concordance between products in the consumer price index (CPI) and commodities in the Harmonized Commodity Description and Coding System. We estimate that over the 2001-2011 period, cumulative inflation would have been 1.17-percentage-points higher for the total CPI had there been no change in the Chinese share of total imports in Canada. This assumes other factors are held constant. The average annual inflation for the total CPI was 2.1 per cent over the 2001-2011 period, implying that annual inflation would have been about 0.12-percentage-points higher if there had not been a surge in imports from China.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.132
GPT teacher head0.303
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueCSLS Research ReportsSame topicGlobal trade and economicsFrench-language works237,207