Dynamic Relationship Between Real Export, Real Import, Real Exchange Rate, Labor Force and Real Gross Domestic Product in Malaysia
Bibliographic record
Abstract
This study examined short run and long run relationship between endogenous and exogenous variables. Specifically, it studied the relationship between real export, real import, labor force participation and real effective exchange rate (REER) and real GDP in Malaysia from 1988 to 2017. These variables were tested in various tests, namely, unit root test, granger causality test, vector autoregressive (VAR), Johansen Juselius test and Error Correction Term (ECT). The result revealed that all variables were non-stationary at the level form and stationary at first difference in ADF unit root test. The findings also exhibited the existence of bilateral relationships between real export and real GDP, real import and real GDP, as well as labor and real GDP. Nonetheless, there were no relationship found between REER and real GDP. On the other hand, in VAR, the lag optimum was lag 10 because it indicated the smallest value of AIC. Moreover, for Johansen Juselius cointegration test, it showed two cointegrated vector at both, 5% and 1%, level in trace test. In addition, Max-Eigen value test indicated two cointegrated vector at 0.05 and one cointegrated vector at 0.01. As for the Wald test, there were long run cointegration relationship between real GDP and its determinants, namely real export, real import, labor and REER. Apparently, Malaysia, as a small open economy, has relied heavily on foreign trade. Consequently, our domestic economic performance is susceptible to the changes in international markets and exchange rate. Therefore, suitable international policy implementation is vital to ensure Malaysian economy will be able to adjust to current global changes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".