The sustainability of current account in the presence of endogenous multiple structural breaks: Evidence from developed and developing countries
Bibliographic record
Abstract
The purpose of this study is to test for the sustainability of current account in 18 developed and 10 developing countries. The stability of the relationship between export (inflows) and import (outflows) is assessed using the tests proposed by Mohitosh Kejriwal and Pierre Perron (2010). In particular, the nature of the long-run relationship, when multiple regime shifts are identified endogenously, is analyzed using the residual-based test of the null hypothesis of cointegration with multiple breaks proposed by Kejriwal (2008). The results clearly indicate that, for all countries, (i) the stability tests reject the null of coefficient stability of the long-run relationship between exports and imports; (ii) the cointegration tests that correspond to the number of breaks selected reject the null of cointegration (weak form of sustainability); and (iii) the strong form of sustainability hypothesis is not supported by the data for all countries in most regimes but not for 20 of 28 countries especially in the last regime (the post-2000 era). For eight countries (Canada, New Zealand, Spain, Brazil, Mexico, South Africa, Thailand, and Turkey), the findings may be perceived as a warning to creditors and policymakers unless there are policy distortions or permanent productivity shocks to the domestic economies.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".