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Record W3037123546 · doi:10.5539/ibr.v13n7p224

Impact of Advancement in Technology, False Conclusion of Real Estate Bubble, Record Low Mortgage Delinquency, Irresponsible Media, U.S. Economic Policy Disaster: Evidence Supporting Eddison Walters Risk Expectation Theory of The Global Financial Crisis of 2007 and 2008

2020· article· en· W3037123546 on OpenAlexvenueno aff
Eddison T. Walters

Bibliographic record

VenueInternational Business Research · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsReal estateFinancial crisisAssertionEconomicsEstateVariable (mathematics)Actuarial scienceFinancial economicsKeynesian economicsFinanceMathematicsComputer science

Abstract

fetched live from OpenAlex

Data analysis in recent studies by the current researcher presented evidence suggesting the existence of a real estate bubble preceding the Global Financial Crisis of 2007 and 2008 was a false conclusion. Data analysis from Walters (2019) resulted in 194.041 Mean Dependent Variable, 0.989 Adjusted R-square, 5.908 Square Error of Regression, and 488.726 Sum-of-Square Residual, from nonlinear regression analysis with the independent variable of “advancement in technology”, which proved to be the most significant factor causing the dependent variable of “home purchase price” to increase preceding the Global Financial Crisis of 2007 and 2008. Based on the findings of data analysis in Walters (2019), the researcher concluded the data confirmed the assertion agreed upon by Alan Greenspan and Ben Bernanke, it was impossible to have a real estate bubble, while citing the Efficient Market Hypothesis in 2005. Subsequent to 2005, alternative attempts to explain the existence of a real estate bubble were made by both former Chairmen of the Federal Reserve Board. Subprime lending and low interest rates were ruled out as the cause of the Global Financial Crisis of 2007 and 2008 in Walters (2019). As a result of the findings from Walters (2019), further investigation to gain an understanding of the impact of how the rapid adaption of advancement in technology influence on the rapid increase in home purchase price preceding the Global Financial Crisis of 2007 and 2008 is required. The purpose of this study is to gain an understanding of the role the rapid adaption of advancement in technology played in the mortgage industry and real estate industry in the United States, and the influence on to the rapid increase in home purchase prices preceding the Global Financial Crisis of 2007 and 2008 as a result of the changes. Insight into the rapid transformation of the mortgage industry and the real estate industry in the United States, and the role the transformation played in the crisis is a critical factor to understanding the impact of advancement in technology on the real estate market in the United States preceding the Global Financial Crisis of 2007 and 2008. Failure to consider the impact of rapid adaption of advancement in technology on the mortgage industry and real estate industry, and the transformation of the real estate market preceding the Global Financial Crisis 2007 and 2008, was a significant error which led to the false conclusion of the existence of a real estate bubble. An understanding of how the rapid transformation of the real estate market as a result of advancement in technology in the United States preceding the Global Financial Crisis of 2007 and 2008, will provide the critical knowledge to evaluate mistakes leading to the false conclusion of a real estate bubble preceding the crisis. The information gained from the current study will help avoid a future financial crisis of the same magnitude.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.051
GPT teacher head0.363
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2020
Admission routes1
Has abstractyes

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