MétaCan
Menu
Back to cohort
Record W4200094431 · doi:10.54605/fec20210302

Do Imports Increase Unemployment? Empirical Estimates That Are Not Model Dependent

2021· article· en· W4200094431 on OpenAlex
Jonathan E. Leightner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFrontiers of Economics in China · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLabor market dynamics and wage inequality
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentEconomicsCzechWageLiberalizationFree tradeInternational economicsDemographic economicsLabour economicsMacroeconomicsMarket economy

Abstract

fetched live from OpenAlex

Some Ricardian models would predict a fall in unemployment with trade liberalization. In contrast, the Heckscher-Ohlin model (Stolper Samuelson Theorem) would predict trade liberalization would cause a fall in wages for labor scarce countries, resulting in greater unemployment if there are wage rigidities. The choice of which theoretical model is used affects the empirical results obtained. This paper produces estimates of the change in unemployment due to a change in imports that are not model dependent. The estimates produced are total derivatives that capture all the ways that imports and unemployment are correlated. I find that unemployment increases with increased imports for Austria, Greece, Japan, Portugal, South Korea, Slovenia, and Sweden, but that unemployment decreases with increased imports for Australia, Belgium, Canada, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Israel, Italy, Latvia, the Netherlands, New Zealand, Norway, Poland, Slovakia, Spain, the UK, and the US.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.258
Teacher spread0.212 · 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