The sources of current account fluctuations in small open economies
Bibliographic record
Abstract
This dissertation investigates the sources of consumption and current account fluctuations of four representative small open economies (Canada, Korea, Mexico, and the United Kingdom) using quarterly data. This study develops an open economy heterogeneous-agent theoretical model, and tests the implications of the model by estimating single equation and structural vector-autoregression (SVAR) empirical models. This dissertation explores interpretations related to liquidity constraints and an overborrowing syndrome (associated with financial liberalization) as the sources of different consumption and current account behavior between developed and developing countries. First, the empirical results suggest that the theoretical model fits well for Mexico compared to other countries. Second, from the single equation models, while Mexico's consumption appears to be strongly affected by disposable income fluctuations. Korea's consumption appears to be strongly affected by external fluctuations. Further, statistical tests for an (unknown) structural break can not find strong evidence for a structural break for all countries. These results do not support the argument for a secular decline in liquidity constraints as a result of economic liberalization. Third, findings from the single equation models on consumption persist in the SVAR framework on the current account. Canada and the United Kingdom's current account fluctuations appear to be mainly explained by domestic net output shocks. In contrast, Mexico's current account appears to be also substantially affected by domestic fiscal balance shocks; and Korea's current account appears to be also significantly affected by external shocks, in addition to domestic net output shocks. Thus, the open economy heterogeneous-agent model appears to reveal qualitative differences in consumption and current account behavior between developed and developing countries.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".