Quantile causality from dollar exchange rate to international oil price

원유가격에 대한 환율의 인과관계 : 비모수 분위수검정 접근

  • Jeong, Kiho (School of Economics and Trade, Kyungpook National University)
  • 정기호 (경북대학교 경제통상학부)
  • Received : 2017.02.22
  • Accepted : 2017.03.23
  • Published : 2017.03.31


This paper analyzes the causal relationship between dollar exchange rate and international oil price. Although large literature on the relationship has accumulated, results are not unique but diversified. Based on the idea that such diversified results may be due to different causality at different economic status, we considers an approach to test the causal relationship at each quantile. This approach is different from the mean causality analysis widely employed by the existing literature of the causal relationship. In this paper, monthly data from May 1987 to 2013 is used for the causal analysis in which Brent oil price and Major Currencies Dollar Index (MCDI) are considered. The test method is the nonparametric test for causality in quantile suggested by Jeong et al. (2012). The results show that although dollar exchange rate causes oil price in mean, the causal relationship does not exist at most quantiles.


Supported by : 경북대학교


  1. Amano, R. and van Norden, S. (1998). Oil price and the rise and fall of the U.S. real exchange rate. Journal of International Money and Finance, 17, 299-316.
  2. Benassy-Quere, A., Mignon, V. and Penot, A. (2007). China and the relationship between the oil price and the dollar. Energy Policy, 35, 5795-5805.
  3. Chaudhuri, K. and Daniel, B. (1998). Long run equilibrium real exchange rates and oil price. Economics Letters, 58, 231-238.
  4. Chen, S. and Chen, H. (2007). Oil price and real exchange rates. Energy Economics, 29, 390-404.
  5. Coudert, V., Mignon, V. and Penot, A. (2008). Oil price and the dollar. Energy Studies Review, 18, 1-18.
  6. Dickey, D. and Fuller, W. (1979). Distribution of the estimators for ar time series with a unit root. Journal of American Statistical Association, 74, 427-431.
  7. Dickey, D. and Fuller, W. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49, 1057-1072.
  8. Granger, C. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424-438.
  9. Hwang, C. (2014). Support vector quantile regression for autoregressive data. Journal of the Korean Data & Information Science Society, 25, 1539-1547.
  10. Hwang, C. (2015). Partially linear support vector orthogonal quantile regression with measurement errors. Journal of the Korean Data & Information Science Society, 26, 209-216.
  11. Hwang, C. and Shim, J. (2016). Deep LS-SVM for regression. Journal of the Korean Data & Information Science Society, 27, 827-833.
  12. Jeong, K., Haerdle, W. and Song, S. (2012). A consistent nonparametric test for causality in quantile. Econometric Theory, 28, 861-887.
  13. Koenker, R. and Bassett, B. (1978). Regression quantiles. Econometrica, 46, 33-50.
  14. Kwiatkowski, D., Phillips, P., Schmidt, P. and Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54, 159-178.
  15. Lee, T. and Yang, W. (2012). Money-income Granger causality in quantiles. Advances in Econometrics, 30, 385-409.
  16. Sadorsky, P. (2000). The empirical relationship between energy futures prices and exchange rates. Energy Economics, 22, 253-266.
  17. Schwert, G. (1989). Tests for unit roots: A Monte Carlo investigation. Journal of Business & Economic Statistics, 7, 147-159
  18. Zhang, Y. and Wei, Y. (2010). The crude oil market and the gold market: Evidence for cointegration, causality and price discovery. Resources Policy, 35, 168-177.