“Global” Productivity Trends, Consumption Expenditures and US Macroeconomic Conditions: A Verification of the “Contagion” Phenomenon
Bibliographic record
Abstract
Panel discussions on global economic performance and the role of economic shocks, often creates the notion that adverse macroeconomic conditions prevailing in dominant economies such as the U.S, tend to have automatic impact on domestic conditions of other economies around the world. This study examined this perceived automatic contagion phenomenon by verifying how key modeled adverse macroeconomic conditions characterizing the U.S economy influence two macroeconomic indicators within selected advanced economies. Empirical estimation via SUR estimation technique verified this contagion phenomenon to some degree; test results suggests adverse macroeconomic conditions such as economic policy uncertainty, inflation expectations etc. can influence core economic indicators within some economies around the world. This study however, also found that not all cross-border interactions exhibits features of the contagion phenomenon, because some economies examined seem to be relatively insulated from modeled cross-border macroeconomic conditions.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".