This paper provides a long-term perspective to the causal linkages between currency dynamics and macroeconomic conditions by utilising a long span data set for the United Kingdom that extends back to 1856 and a time-varying causality testing methodology that accounts for the nonlinearity and structural breaks. Using unemployment fluctuations as a proxy for macroeconomic conditions and wavelet decompositions to obtain the fundamental factor that drives excess returns for the British pound, time varying causality tests based on alternative model specifications yield significant evidence of causal linkages and information spillovers across the labour and currency markets over the majority of the sample. Causal effects seem to strengthen during the Great Depression and later following the collapse of the Bretton Woods system, highlighting the role of economic crises in the predictive linkages between the two markets. While the predictive role of currency market dynamics over unemployment fluctuations reflects the effect of exchange rate volatility on corporate investment decisions, which in turn, drives subsequent labour market dynamics (e.g. Belke & Gross (2001); Belke & Kaas (2004); Feldman (2011); among others), we argue that causality in the direction of exchange rates from unemployment possibly reflects the signals regarding monetary policy actions, which in turn, spills over to financial markets. Overall, the findings indicate significant information spillovers across the labour and currency markets in both directions with significant policy making implications
Download full text from publisher
More about this item
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
NEP fieldsThis paper has been announced in the following NEP Reports:
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ctn:dpaper:2020-01. 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: (Kevin Kotze). General contact details of provider: http://edirc.repec.org/data/seuctza.html .
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.
We have no references for this item. You can help adding them by using 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 RePEc Author Service 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.