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Record W3163861295 · doi:10.5539/ibr.v14n6p24

The Financial Performance on Asset Quality of Insurance Industry in Egypt (Panel Data Analysis)

2021· article· en· W3163861295 on OpenAlexvenueno aff
Salah Mohamed Eladly

Bibliographic record

VenueInternational Business Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicInsurance and Financial Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsEconometricsVariablesPanel dataMarket liquidityProfitability indexActuarial scienceStatisticRobustness (evolution)Equity (law)Return on assetsBusinessEconomicsStatisticsFinanceMathematics

Abstract

fetched live from OpenAlex

This study is an attempt to analyze the  impact of the financial performance on asset quality of insurance industry in Egypt as  applied on a sample of 19 insurance companies over the period 1999-2019.The financial performance measured by profitability (return on equity-return on investment) and liquidity results show that there is a significant negative linear relationship between the independent variable in terms ofX3, and the dependent variable; y, at a significant level less than (0.01), while there is no significant linear relationship between the independent variable of X1,X2, and dependent variable; y at a significant level greater than (0.05) . The study methodology used panel data analysis according to ARDL model and OLS, beside the robustness check supports these results using the Jarque-Bera test and the Durbin-Watson test statistic

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)0.004
metaresearch head score (Gemma)0.003
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 score0.093
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.271
GPT teacher head0.398
Teacher spread0.127 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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