An Input Output Analysis Model for the Spanish Economy Based on Working Hours
Bibliographic record
Abstract
In labor economics, the input-output models have had little development. In the second half of the 20th century, various input-output analyses focused on the use of time in the German economy were initiated and resulted in the Input output tables of time (TIOT). However, despite the fact that this methodology has been included in the manual published by Eurostat on the elaboration of input-output frameworks, there is little research and analysis with this type of tables. In this study we obtained the TIOT for the Spanish economy in 2016 and on the basis of the analysis of Passinetti and Saffra on interindustry relationships,, it presents an analysis of input-output on the basis of the TIOT which gives rise to an open model of Leontief, and a model of shadow prices for the hours worked, which can be used for the analysis of the impacts on the economy that lead to changes in the distribution of hours worked in consequence of the extension of new technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".