The effect of the Economic Policy Uncertainty on the development of the North American index and the Spillover effect in Canada and Japan
Bibliographic record
Abstract
This dissertation aims to study the effect of the political uncertainty index on the stock market index behavior. Considering the available data, it was decided to study the effect that the EPU has on the development of the S&P500, the North American stock market index, and the contagion effect in countries that had some relation, either economic or geographic, such as Japan and Canada. To this end, the dissertation was divided into two parts. In the first part we analyze the influence of the EPU only in the United States, and in the second part we expand the study to the other countries already mentioned. Through the time-varying LA-VAR Granger causality test we realize that fiscal and monetary policies are the ones that present greater causality with respect to the chosen North American index. The second part brings us similar results in agreement with the existing literature. Through Markov-Switching regression we prove that there is a contagion relation between the chosen North American nominees and the development of the chosen indexes for those countries. The results of the ARCH and GARCH models show us in a first step that the EPU of the United States was not statistically significant while the EPU of Japan was shown to influence the behavior of the TSX exchange. The GARCH models showed no statistical evidence of this relationship. Overall, this paper shows us the importance of the ability of political and economic decisions to be as clear as possible to avoid the opposite of desirable economic outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".