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Record W155886404

Impact of the Exchange Rate Regime Change on the Value of Bangladesh Currency a

2009· article· en· W155886404 on OpenAlexaff
Asad Karim Khan Priyo

Bibliographic record

VenueMunich Personal RePEc Archive (Munich University) · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExchange rateCurrencyExchange-rate regimeEconomicsLiberian dollarValue (mathematics)Order (exchange)Context (archaeology)Monetary economicsFloating exchange rateInternational economicsGeographyMathematicsFinanceStatistics
DOInot available

Abstract

fetched live from OpenAlex

Two distinctively different exchange rate regimes have been in place in Bangladesh – a fixed exchange rate regime from January 1972 – May 2003 and a floating exchange rate regime since June 2003. Since the change in regime, the value of Bangladesh currency ‘Taka’ has fallen by more than 20% against the US Dollar during a period when the US Dollar itself has been losing value. The objective of this paper is to analyze whether the exchange rate regime change in Bangladesh has had any significant impact on the value of its currency i.e. whether the regime change is associated with the loss in the value of Taka. The fact that during the fixed regime, Bangladesh pursued an active exchange rate policy as reflected by the policies of Bangladesh Bank during that period is what makes the question worth asking. In one way, this paper tests the efficiency of Bangladesh Bank in terms of pricing its currency during the fixed regime. In the process, the paper also tries to identify the variables that play important roles in determining the exchange rate of Taka. In order to provide context; the exchange rate system in Bangladesh – its past, its present; the causes of the change in the system and a comparative analysis of the systems have been briefly discussed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.229
Teacher spread0.151 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2009
Admission routes1
Has abstractyes

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