Import‐economic growth nexus: ARDL approach to cointegration
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the relationship between import and economic growth for 62 countries. Design/methodology/approach The paper applies autoregressive distributed lag model (ARDL) for long‐run relation and Granger causality test, in order to detect the direction of short‐run and long‐run causal relationship. Findings The results indicate that the long‐run relationship exists in the USA, the UK, Japan, Iceland, Canada, Italy, Algeria, Brazil, Chile, Colombia, Cuba, Gabon, Malaysia, Mexico, Peru, South Africa, Uruguay, Bolivia, Cameroon, Cote d'Ivoire, Ecuador, Egypt, El Salvador, Guatemala, Honduras, India, Lesotho, Nicaragua, Papua New Guinea, Thailand, Bangladesh, Benin, Chad, Congo, Gambia, Kenya, Madagascar, Togo, Zambia and Zimbabwe when economic growth is dependent variable. This result confirms the importance of import in the process of sustainable economic growth of these countries. In alternative combination when import is dependent variable, the long‐run relationship is found in the USA, the UK, Japan, Finland, Iceland, Canada, Italy, Brazil, Cuba, Dominican Republic, Iran, Malaysia, Mexico, Peru, South Africa, Bolivia, Cameroon, Guatemala, Honduras, India, Indonesia, Lesotho, Morocco, Nicaragua, Pakistan, Philippines, Senegal, Sudan, Swaziland, Thailand, Tunisia, Bangladesh, Benin, Burkina Faso, Chad, Congo, Gambia, Kenya, Madagascar, Malawi, Mali, Mauritania, Togo and Zambia. These findings confirm the importance of source of economic growth for import. On the other hand, the results of Granger causality test indicate mixed results but the importance is that in the case of higher income countries, there is unidirectional long‐run causality found from import to economic growth (except the USA, Iceland and Italy), and bidirectional long‐run causal relationship exists between import and economic growth in low income countries except Madagascar and Mauritania. Originality/value This paper provides the largest sample, including 62 countries, examining the relationship between import and economic growth, from 1971 to 2009.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".