A Non-Linear Approach to Current Account Sustainability—The Cases of Germany, China, and the USA
Bibliographic record
Abstract
This paper examines the sustainability of the current account balances for three leading economies that play significant roles in global financial and geopolitical developments: Using the concept of sustainability as the ability of an economy to meet its long-term intertemporal budget constraint, the analysis evaluates whether the current accounts of these three economies can maintain this condition without requiring substantial policy interventions or significant changes in private sector behavior. The stationarity of the current account is considered a sufficient condition for testing the sustainability of the current account balance. However, it is argued that the common assumption of a linear process for the current account under the alternative hypothesis of stationarity may not accurately reflect reality, as the current account may exhibit non-linear behavior. Therefore, both linear and non-linear unit root tests are employed to investigate current account sustainability. The results of the unit root tests indicate that the current account balances of Germany, China, and the United States are unsustainable. These findings have significant implications for the economic stability and policy direction of these major 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".