DETECTING SCAPEGOAT EFFECTS IN THE RELATIONSHIP BETWEEN EXCHANGE RATES AND MACROECONOMIC FUNDAMENTALS: A NEW APPROACH
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Bibliographic record
Abstract
This paper presents a new testing method for the scapegoat model of exchange rates. A number of steps are implemented to determine whether macro-fundamentals are scapegoats for the evolution of exchange rates. Estimation is conducted using a Bayesian Gibbs sampling approach applied to eight countries (five developed and three emerging) versus the USA over the period 2002 Q 1–2014 Q 4. The macro-fundamentals that we consider are real GDP growth, the inflation rate, the long-run nominal interest rate, and the current account to GDP ratio. We calculate the posterior probabilities that these macro-fundamentals are scapegoats. For the inflation rate, these probabilities are considerably higher than the imposed prior probabilities of ½ in five out of eight countries (in particular, the Anglo-Saxon economies).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it