A Johansen Cointegration Test for the Relationship between Remittances and Economic Growth of Japan
Bibliographic record
Abstract
Remittance inflows have been a key stimulus to economic growth of many developing countries. There is scant literature available on the impact of remittance inflows and outflows on the economic growth of the large developed countries. For instance, there is little literature on the impact of remittance inflows and outflows on the economic growth rate of Japan. Hence this research objective of this paper is to investigate the relationship between ‘remittance inflows’ and ‘outflows’ on the ‘economic growth rate’ of Japan. The paper by utilizing the World Bank data set and the econometric model namely the Granger Causality Model to test and analysis the impact of remittance inflows and outflows on the economic growth rate of Japan. The findings show that in the long run, a 1% increase in remittance outflows will decrease GDP growth rate by 0.000793%. In the short run, a 1% increase in remittance outflows and inflows will decrease GDP growth rate by 0.000599% and 0.000327% respectively. The Japanese government should encourage retired Japanese workers to return to the labour market and effectively contribute to the workforce and retired workers can be re-trained so that less foreign migrant workers are needed and this will reduce remittance outflow.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".