Measuring exchange rate flexibility by regression methods

Bleaney, Michael; Tian, Mo

doi:10.1093/oep/gpw029

Cited by 16 publications

(37 citation statements)

References 11 publications

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“…In this Section we generate alternative statistics based on the residuals from a regression similar to that of Bleaney and Tian (2017). The point of this exercise is that the difference between these measures is purely statistical; the treatment of realignments and the method for estimating the central rate are identical, so important conceptual differences have been eliminated.…”

Section: Comparing Alternative Statisticsmentioning

confidence: 99%

“…The three schemes that we focus on are those of Shambaugh (2004), Reinhart and Rogoff (2004) and Bleaney and Tian (2017).…”

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confidence: 99%

“…The scheme of Bleaney and Tian (2017) [hereafter termed BT] presents a flexibility index based on the root mean square residual (RMSE) from a regression of the change in the log of the exchange rate against a chosen numéraire currency on the change in the log of the US dollar and of the euro against the same numéraire currency. This regression was originally suggested by Frankel and Wei (1995) for identifying basket pegs.…”

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confidence: 99%

“…The statistics are based on a regression identical to that of Bleaney and Tian (2017), except that we extend the period from twelve to 24 months. This is because with twelvemonth windows there is a maximum of only nine degrees of freedom (and only eight if a realignment is identified), which is rather a small number from which to generate accurate statistics.…”

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confidence: 99%

“…To generate 8 Alternative numeraire currencies to the Swiss franc may be used; see the discussion in Bleaney and Tian (2017). 9 For details see Bleaney and Tian (2017 corresponds directly to a target zone of ±2%, and a threshold of 0.02 corresponds to a target zone of ±1%. We label the classifications thus generated respectively RANGE-4, RMSE-1, RANGE-3, RMSE-0.8, RANGE-2 and RMSE-0.6.…”

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confidence: 99%

See 4 more Smart Citations

De Facto Exchange Rate Regime Classifications: An Evaluation

2016

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There exist several statistically-based exchange rate regime classifications that disagree with one another to a disappointing degree. To what extent is this a matter of the quality of the design of these schemes, and to what extent does it reflect the need to supplement statistics with other information (as is done in the IMF's de facto classification)? It is shown that statistical methods are good at the basics (distinguishing some type of peg from some type of float), but less helpful in other respects, such as determining whether a float is managed, particularly for countries that are not very remote from their main trading partners. Different measures of exchange rate volatility have been used but are not primarily responsible for differences between classifications. The theoretical underpinning of particular classification schemes needs to be more explicit.

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Section: Comparing Alternative Statisticsmentioning

confidence: 99%

“…The three schemes that we focus on are those of Shambaugh (2004), Reinhart and Rogoff (2004) and Bleaney and Tian (2017).…”

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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De Facto Exchange Rate Regime Classifications: An Evaluation

2016

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The Tunisian exchange rate regime: Is it really floating?

Bouabidi

2020

Int. J Fin Econ

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While the Tunisian authority claims to adopt a floating exchange regime, the International Monetary Fund (IMF) classifies it as a rather crawl‐like regime. This paper aims at studying the Tunisian exchange rate regime over the post‐revolution period. It uses daily data from 2010 to 2019. The empirical results show that the Tunisian de facto regime is broadly consistent with the IMF classification. Nevertheless, the IMF stated that in 2018 the EUR is the only anchor, but this study shows that from 2017 the implicit weight of the USD becomes higher than the EUR. Most of the time, there is a discrepancy between the regime claimed by the Tunisian authority and the de facto regime detected by the model. Annual regressions, the Chow, and the Bai‐Perron breakpoint tests show that the Tunisian de facto regime is not stable.

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Exchange Rate Flexibility: How Should We Measure It?

Bleaney

Tian

2020

Open Econ Rev

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This paper first examines some recent exchange rate classification schemes. There is little evidence of a trend towards greater agreement between schemes. There is a probability of between 16 and 28% that a peg in one classification scheme is coded as a float in a different scheme, or vice versa. This probability is much smaller for the tightest forms of peg and the most volatile floats. Continuous indices of exchange rate flexibility are analysed and shown to have significant potential, despite the lack of interest in them shown in previous research.

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Measuring exchange rate flexibility by regression methods

Cited by 16 publications

References 11 publications

De Facto Exchange Rate Regime Classifications: An Evaluation

De Facto Exchange Rate Regime Classifications: An Evaluation

The Tunisian exchange rate regime: Is it really floating?

Exchange Rate Flexibility: How Should We Measure It?

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