A multicountry use of input -output tables to test the Heckscher -Ohlin theorem accounting for actual imports
Bibliographic record
Abstract
This dissertation presents a modification of the original framework implemented by Wassily Leontief to test the validity of one of the most venerable theories of international trade. Most major empirical investigations of the Heckscher-Ohlin theorem using the Leontief approach have concentrated on the limited framework. In this dissertation, we empirically examine the determinants of the structure of foreign trade for the most developed nations (i.e., Australia, Canada, Denmark, France, Germany, Italy, Japan, the United Kingdom and the United States) over the period 1968–1996. The data set used represents the most extensive data set available to document the pattern of industrial specialization and factor endowment differences. Our analyses are based on the factor content version of the Heckscher-Ohlin model using first the original Leontief method for the United States and for each of the remaining countries mentioned. Then, the input-output tables are used to measure the capital-labor content of each industry. This approach allows us to detect the presence of factor intensity reversal, the only assumption that cannot be relaxed in the Heckscher-Ohlin theory. Last, we introduce a modification in the balance equations of the general system used as a framework to test the validity of the Heckscher-Ohlin theory. The results of this study should be enriching for international trade economists. The study does validate the use of the underlying general equilibrium model as originally intended by Wassily Leontief but never implemented due to lack of concrete quantitative information. The principal premise of the Heckscher-Ohlin model, formerly questioned, has proven to hold for all or the majority of the years of our study resulting in trade patterns that promote prosperity within a nation.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".