An Empirical Analysis of Exports between Malaysia and TPP Member Countries: Evidence from a Panel Cointegration (FMOLS) Model
Bibliographic record
Abstract
The aim of this study is to investigate empirically the role of Malaysian exports to TPP countries towards economic growth of Malaysia from 1997 to 2012. The results of this study confirm that Malaysian exports to TPP countries contribute in economic growth of Malaysia. Therefore, the result of this study is obtained through the empirical investigation of the model. Mainly, empirical investigation is based on FMOLS model but some preliminary tests are also performed. The results of unit root test presents that all Variables are non-stationary at level I(0) and become stationary after first difference I(1). In addition, results of Kao’s panel cointegration shows that all the variables are cointegrated. Furthermore, Results of FMOLS confirms that out of all the variables included in the model, GDP, TRGDP and ER have significant effect on the exports. ECM panel unit root test were applied to confirm the stability of FMOLS. According to the unit root test of the residuals of FMOLS model, it can be confirmed that the long run results are not spurious. Results of Panel ECM show that out of all variables GDP and TRGDP are positively effect on exports. Finally, results of Granger Causality show that only CPI, GDP and TRGDP are cause exports in Malaysia. The government of Malaysia through understood the importance of exports with TPP member countries to boost economic growth. The latter not only contributes to economic growth through capital formation but also promotes trade activity by making financial resources available at lower cost; attracting foreign direct investment as well as facilitating development of advanced technology. Moreover, this study not only contribute to the exports and economic growth literature but also will guide the policy maker to chalk out right, effective and appropriate policy in order to improve exports between Malaysia and TPP countries.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".