Bibliographic record
Abstract
The global pandemic of COVID-19 continues in September 2022, and socioeconomic activities are in great turmoil.In Japan, various socioeconomic activities were restricted due to the declaration of a state of emergency and measures to prevent the spread of the virus four times, and the flow of people was curbed.The domestic economy was in a slump, and domestic GDP fell significantly in the second quarter of 2020.However, the government and the Bank of Japan implemented large-scale monetar y easing policies, special fixed-price benefits, temporar y leave support and benefits in response to the new coronavirus infection, employment adjustment subsidies, and other support policies, and the monetary base expanded rapidly.As a result, domestic GDP has shown a moderate recovery trend since the third quarter of 2020.United States is in a similar situation, with a temporary economic downturn early in the COVID-19 pandemic.However, the monetary base expanded rapidly due to economic policies centered on cash transfers, and the economy continued to recover from the third quarter of 2020.Turning to the stock market, the Nikkei 225 Stock Average temporarily topped 30,000 yen, the highest price since the collapse of the bubble economy.In U.S. stock market, the Dow Jones Industrial Average hit an all-time high, and the sense of overheating increased.In Japan, the Bank of Japan has been continuing its monetary easing policy to date in order to achieve its price stability target.In U.S., however, the economy has been recovering and the consumer price index has risen sharply, increasing the sense of caution about inflation, and the Federal Reser ve Board has shifted to a tighter monetar y policy.Due to the reversal of monetary policy between Japan and U.S., the interest rate differential has widened and the dollar/yen exchange rate has rapidly shifted to depreciation of the yen.This paper attempts to analyze and examine fluctuations in the Nikkei Stock Average in an environment where the dollar/yen exchange rate shifts to depreciation of the yen.Specifically, we construct a state-space model from the data of the Nikkei Stock Average, the dollar/yen exchange rate, and the Dow Jones Industrial Average, solve the model using MCMC, and discuss the results.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.018 |
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".