Abstract
Recent studies have analysed the ability of measures of uncertainty to predict movements in macroeconomic and financial variables. The objective of this paper is to employ the recently proposed nonparametric causality-in-quantiles test to analyse the predictability of returns and volatility of sixteen U.S. dollar-based exchange rates (for both developed and developing countries) over the monthly period of 1999:01–2012:03, based on information provided by a news-based measure of relative uncertainty, i.e., the differential between domestic and U.S. uncertainties. The causality-in-quantile approach allows us to test for not only causality-in-mean (1st moment), but also causality that may exist in the tails of the joint distribution of the variables. In addition, we are also able to investigate causality-in-variance (volatility spillovers) when causality in the conditional-mean may not exist, yet higher order interdependencies might emerge. We motivate our analysis by employing tests for nonlinearity. These tests detect nonlinearity, as well as the existence of structural breaks in the exchange rate returns, and in its relationship with the EPU differential, implying that the Granger causality tests based on a linear framework is likely to suffer from misspecification. The results of our nonparametric causality-in-quantiles test indicate that for seven exchange rates EPU differentials have a causal impact on the variance of exchange rate returns but not on the returns themselves at all parts of the conditional distribution. We also find that EPU differentials have predictive ability for both exchange rate returns as well as the return variance over the entire conditional distribution for four exchange rates.
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Notes
Complete details of the unit root tests are available upon request from the authors.
We thank Jonathan Brogaard for providing us with the EPU data. Note that, though Brogaard and Detzel (2015) created the EPU for 21 countries in an earlier version of the paper, they only concentrated on the US stock market in the published version.
Theoretically, measures of uncertainty should be stationary. However, statistically, it could deviate from this due to the sample period considered. But, the unit root tests revealed that the natural logarithm of the EPUs on their own as well as in differential form, did not contain unit roots, and hence, could be used in levels in our analysis. Complete details of the unit root tests are available upon request from the authors.
One exception is in Fig. 14 for the variance of the Swedish Krona exchange rate. EPU explains the variance at the 0.45 to 0.55 quantiles.
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Balcilar, M., Gupta, R., Kyei, C. et al. Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test. Open Econ Rev 27, 229–250 (2016). https://doi.org/10.1007/s11079-016-9388-x
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DOI: https://doi.org/10.1007/s11079-016-9388-x
Keywords
- Economic policy uncertainty
- Exchange rate returns
- Volatility
- Nonparametric quantile causality
- Developed and emerging markets