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Record W4372361298 · doi:10.54691/bcpbm.v45i.4876

The Lost Decade: Research on the Japanese Asset Price Bubble

2023· article· en· W4372361298 on OpenAlexaff
Enping Shen

Bibliographic record

VenueBCP Business & Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsTerry Fox Research Institute
Fundersnot available
KeywordsQuantitative easingEconomic bubbleRecessionEconomicsEconomic miracleGreat DepressionAsset (computer security)Interest rateOverheating (electricity)Economic recoveryMonetary policyDeflationMonetary economicsEconomyEconomic policyMacroeconomicsCentral bankGeographyPolitical science

Abstract

fetched live from OpenAlex

Due to the burst of Japanese asset price bubble in 1989s, Japan’s economy has started a clearly great depression, specifically manifest as downturn in GDP, decline in economic activity, decrease in the general price level, and manufacturing sector in recession. The burst of bubble directly shows as expansion on credit and money supply, overheating in assets market and economic activity. This paper aims on elaborating and analyzing Japanese unique economic development history after Second World War. This paper also focuses on how the Japanese economic miracle happened and how does Japanese economic miracle came into asset price bubble. Based on those economic policies implemented by Japanese government, including zero interest rate policy (ZIRP), negative interest rate, quantitative easing (QE), qualitative quantitative easing (QQE), and the three arrows of Shinzo Abe, this paper analyzes those policies in economic direction. This paper also researches on some other potentials and secondary influences on Japanese economy, such as Japanese corporate system since 1600s, the involvement of the USA, the plaza accord, several Japanese bank’s bad loans.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.012

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.

Opus teacher head0.113
GPT teacher head0.321
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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