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Record W2965285205

The determinants of inflation rate in Malaysia / Solehah Mohamad

2015· article· en· W2965285205 on OpenAlexaboutno aff
Solehah Mohamad

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsInflation (cosmology)Exchange rateEconometricsUnemploymentMoney supplyQuarter (Canadian coin)Gross domestic productVariablesReal interest rateVariable (mathematics)Regression analysisInflation rateMacroeconomicsMonetary economicsInterest rateStatisticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

The main purpose of this research is to examine the determinant factors of inflation in Malaysia. The relationship between macroeconomic factors namely money supply, unemployment rate, exchange rate, gross domestic product and oil price with inflation are studied. This research study covers quarterly data for the time period for the period of first quarter 2007 to fourth quarter 2014. The time series data for the entire dependent and independent variables are to be non-stationary at the level but stationary at first difference. The results show both long-run and short-run relationships between money supply, unemployment rate, exchange rate, gross domestic product and oil price with inflation. The study employs Multiple Linear Regression Method to analyze the relationship between independent and dependent variable. The time series data are collect by quarterly basis from the data stream which is the main source to obtain the quantitative data. The scope of study is based on the macroeconomic factors in Malaysia which the study will be focus on the influence of these factors towards inflation in Malaysia. In this research, the expected result is the independent variables will have significant and insignificant relationship with the inflation in Malaysia.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.220
Teacher spread0.202 · 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
Published2015
Admission routes1
Has abstractyes

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