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Record W1483405122 · doi:10.34989/sdp-2011-5

External Stability, Real Exchange Rate Adjustment and the Exchange Rate Regime in Emerging-Market Economies

2021· preprint· en· W1483405122 on OpenAlexaff
Olivier Gervais, Lawrence Schembri, Lena Suchanek

Bibliographic record

VenueEconstor (Econstor) · 2021
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsBank of Canada
Fundersnot available
KeywordsExchange rateEconomicsEmerging marketsMonetary economicsStability (learning theory)Exchange-rate regimeMacroeconomics

Abstract

fetched live from OpenAlex

In emerging-market economies, real exchange rate adjustment is critical for maintaining a sustainable current account position and thereby for helping to reduce macroeconomic and financial instability. The authors examine empirically two related hypotheses: (i) that real exchange rate flexibility and adjustment promotes external stability, and (ii) that a flexible nominal exchange rate facilitates real exchange rate adjustment. Based on an event-study analysis for a large set of emerging-market economies over the period 1975–2008, the authors find that real exchange rate adjustment has contributed significantly to reducing current account imbalances. The adjustment of current account deficits in countries with a fixed exchange rate regime does not typically occur through the classical adjustment mechanism, but as a consequence of exchange rate crises, where the nominal exchange rate collapses and there are substantial costs in terms of forgone output. Vector-error-correction results support the findings of the event study; namely, in the long run the real exchange rate movements facilitate current account adjustment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.027
GPT teacher head0.237
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

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