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Record W4295064860 · doi:10.1111/roie.12634

Testing the validity of purchasing power parity for China: Evidence from the Fourier quantile unit root test

2022· article· en· W4295064860 on OpenAlexaff
Kenneth S. Chan, Jennifer T. Lai, Xiaoyi Liang

Bibliographic record

VenueReview of International Economics · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsMcMaster University
FundersNatural Science Foundation of Guangdong ProvinceNational Natural Science Foundation of ChinaMinistry of Education of the People's Republic of ChinaState of New Jersey Department of Education
KeywordsPurchasing power parityEconomicsUnit rootQuantileEconometricsPrice indexUnit root testChinaRelative purchasing power parityFinancial economicsMonetary economicsCointegrationGeographyExchange rate

Abstract

fetched live from OpenAlex

Abstract We revisit the purchasing power parity (PPP) between China and its five major trading partners, namely European Union, United States, Brazil, Japan, and Korea. Conventional unit root tests with structural breaks have mostly failed to validate the PPP. Apart from using CPI as the price index, the tradable‐goods price index is also used to test the PPP hypothesis (Balassa–Samuelson effect). Using the Fourier quantile unit root test for the potential structural breaks and non‐Gaussian distribution reveals strong evidence that the PPP holds between China and its five major trading partners.

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)0.008
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.104
GPT teacher head0.295
Teacher spread0.191 · 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 designSimulation or modeling
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

Citations4
Published2022
Admission routes1
Has abstractyes

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