Purchasing Power Parity and Degree of Openness in Latin America: A Panel Analysis
Bibliographic record
Abstract
We move beyond the all or nothing purchasing power parity (PPP) proposition that has been the norm in previous literature. We test whether inflation, nominal exchange rate volatility, and trade and financial openness influence the stationarity of real exchange rates on a sample of Latin American and Caribbean countries plus Canada during the post Bretton-Woods era. Countries with high inflation and high exchange rate volatility are more likely to support PPP. Classifying the countries by traditional trade openness is not possible to find stationarity consistent with the findings of Alba and Papell (2007) that more open countries are more likely to support PPP. However, when trade openness is parameterized by “relative weight trade intensity” (RWTI), which provides a bi-dimensional approach to international trade weight, we find that higher trade openness leads to higher support of PPP. Westerlund (2007) cointegration error correction model (ECM) tests in panels indicate that financial openness supports PPP only when national debt is not considered. Financially open countries and those that open their borders to trade are more likely to have a mean reversion of exchange rates. These outcomes are relevant to emphasize the benefits of trade and financial openness in economies close to the United States.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".