Bibliographic record
Abstract
This research is mainly focused on the time-inconsistency during policy making process. It contains three chapters as follows: Chapter One is to research into the time-inconsistency problem in policy making with extensive form games. The paper divides the game into four scenarios: one-stage independent game, one-stage forecasting game, finite stage forecasting game and infinite period game. The first two games show that neither government nor public want to be type 1 and government always has an incentive to deviate from announced policy. The last two games are mainly focused on the possibilities that both players want to randomize their strategies. The games are able to conclude that players only randomize under certain conditions. Chapter Two is to prove the existence of time-inconsistent monetary policy in the U.S. empirically by applying both non-parametric method and rolling estimation for time varying analyses along with the asymmetric policy preference model, this paper proposes that with almost every recession since 1960, the rolling method reaches a break point shortly before or right at the recession date and that the non-parametric method reaches a peak for every recession that is not caused by supply shock. In addition, this paper uses the chain-weighted PCE index to conclude that there exists time-inconsistent policy preference over different recession periods, and also to compare results with the chain-weighted GDP index. The study discovers that the PCE index in general will result higher targeted inflation rate than the GDP index, and policy preferences are different during pre- and post-recessions with both indexes. Chapter Three is extending the empirical analysis to different countries by studying the policy preferences of pre- and post-recession periods. Most countries depict their policy preferences as time-inconsistent. Moreover, by adjusting the non-stationarity problem in the data during the first-stage regression, the paper is able to capture the differences between both analyses. The study concludes that only Italy, Netherlands and Canada are not affected by non-stationarity problem that much and both analyses can reach a general consistent results; whereas the rest countries are greatly affected by the non-stationarity problem, especially the US and UK.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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; both teacher heads agree on what is shown here.
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".