Stationarity of Real Exchange Rates in the “Fragile Five”: Analysis with Structural Breaks
Bibliographic record
Abstract
In this study the stationarity of monthly real exchange rate data for the “fragile five” countries which are among the emerging market economies, is analyzed for the period of 2003:01-2015:10, using traditional unit root tests and unit root tests with structural breaks. According to the results of traditional Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root test results, it has been determined that the real exchange rate series of the fragile five countries had a unit root and therefore the Purchasing Power Parity (PPP) hypothesis does not hold true in these countries. The results of a Zivot-Andrews unit root test, which allows for a single structural break, show that real exchange rate series were stationary for Brazil and India, and hence the PPP hypothesis is valid in these countries. According to the results of a Lee-Strazicich unit root test, which allows for two structural breaks, it has been concluded that the hypothesis is valid only for India. Likewise, using the Carrion-i- Sivestre (CS) unit root test, which allows for five structural breaks in the time series, it has been determined that only South Africa’s and India’s real exchange rate series are not stationary, and therefore the PPP hypothesis is not valid for these countries. In line with the results of the CS unit root test it can be claimed that, due to the fact that South African and Indian central banks are not under the pressure of establishing exchange rate stability, they have the possibility of implementing an independent monetary policy.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".