Classifying Exchange Rate Regimes by Regression Methods
A new and easily implemented regression method is proposed for distinguishing floating from pegged regimes, whilst simultaneously identifying anchors of pegged currencies. The method can distinguish pegs with occasional devaluations from floats, and can be used to generate annual regime classifications. The method largely confirms the accuracy of the IMF’s de facto classification, but also shows that a significant minority of managed floats is close to being US dollar pegs. Even flexible managed floats have a strong tendency to track the US dollar.
|Date of creation:||Apr 2014|
|Contact details of provider:|| Postal: School of Economics University of Nottingham University Park Nottingham NG7 2RD|
Phone: (44) 0115 951 5620
Fax: (0115) 951 4159
Web page: http://www.nottingham.ac.uk/economics/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:not:notecp:14/02. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.