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Copulas for Modeling the Relationship Between Inflation and the Exchange Rate

  • Laila Ait Hassou
  • Fadoua BadaouiEmail author
  • Okou Guei Cyrille
  • Amine Amar
  • Abdelhak Zoglat
  • Elhadj Ezzahid
Conference paper
  • 1.1k Downloads
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

Copulas are useful tools for formalizing the dependence structure between variables. They have proven to be very valuable in economics, where the dependence plays a key role. In this chapter, we use copulas to analyze the dependence between inflation and US/Euro exchange rates in the Euro area, during different periods. We first explore the dependence between the variables using a nonparametric approach. Then, we select an appropriate parametric copula for each period. Results confirm the sensibility of copulas to macroeconomic fluctuations that occur during the analyzed periods.

Keywords

Copulas Exchange rate Goodness-of-fit tests Inflation Nonparametric approaches 

References

  1. 1.
    International Labour Office (ILO), International Monetary Fund (IMF), Organization for Economic Co-operation and Development (OECD), Statistical Office of the European Communities (Eurosat), United Nations (UN) and the World Bank: Consumer price index manual. Theory and practice. International Labour Office. Geneva (2004). ISBN, 92–2–113699–XGoogle Scholar
  2. 2.
    Chollete, L., Ning, C.: The Dependence structure of macroeconomic variables in the US. Working Papers Series 0204, University of Ryerson (2009)Google Scholar
  3. 3.
    Munyeka, W.: An in-depth look at economic growth and employment in post-apartheid South Africa: analysis and policy implications. J. Educ. Soc. Res. 4(3) MCSER, Rome-Italy (2014)Google Scholar
  4. 4.
    Fitzgerald, T.J., Nicolini, J.P.: Is there a stable relationship between unemployment and future inflation? Evidence from U.S. Cities. Working Paper 713, Federal Reserve Bank of Minneapolis Research Department (2014)Google Scholar
  5. 5.
    Arize, A.C., Malindretos, J., Nippani, S.: Variations in exchange rates and inflation in 82 countries: an empirical investigation. North Am. J. Econ. Fin. 15, 227–247 (2004)CrossRefGoogle Scholar
  6. 6.
    Naz, F., Mohsin, A., Zaman, K.: Exchange rate pass-through in to inflation: new insights in to the cointegration relationship from Pakistan. J. Econ. Model. 29, 2205–2221 (2012)CrossRefGoogle Scholar
  7. 7.
    Xiongtoua, T., Sriboonchitta, S.: Analysis of volatility and dependence between exchange rate and inflation rate in Lao people’s democratic republic using copula-based GARCH approach. Model. Depend. Econ. 251, 201–214 (2014)Google Scholar
  8. 8.
    Kano, T.: Exchange rates and fundamentals: a general equilibrium exploration, Hitotsubashi Institute for Advanced Study, Discussion Paper HIAS–E–19 (2016)Google Scholar
  9. 9.
    Burstein, A., Gopinath, G.: International prices and exchange rates. In: Handbook of International Economics, vol. 4, pp. 391–451. North Holland/Elsevier, London (2014)Google Scholar
  10. 10.
    Engel, C.: Exchange rates and interest parity. In: Handbook of International Economics, vol. 4, pp. 453–522. North Holland/Elsvier, London (2014)Google Scholar
  11. 11.
    Kole, E. et al.: Selecting copulas for risk management. J. Bank. Fin. https://doi.org/10.1016/j.jbankfin.2006.09.010.(2007)
  12. 12.
    Grégoire, V., Genest, C., Gendron, M.: Using copulas to model price dependence in energy markets. Energy Risk 5, 58–64 (2008)Google Scholar
  13. 13.
    Genest, C., Gendron, M., Bourdeau-Brien, M.: The advent of copulas in finance. Eur. J. Fin. 15(7/8), 609–618 (2009)CrossRefGoogle Scholar
  14. 14.
    Frees, E.W., Valdez, E.A.: Under standing relationships using copulas. North Am. Actu. J. 2, 1–25 (1998)CrossRefGoogle Scholar
  15. 15.
    Joe, H.: Multivariate models and dependence concepts. In: Monographs on Statistics and Applied Probability, vol. 73. Chapman Hall, London (1997)Google Scholar
  16. 16.
    Nelsen, R.B.: An Introduction to Copulas, 2nd edn. Springer, New York (2006)zbMATHGoogle Scholar
  17. 17.
    Sklar, A.: Fonctions de répartition á n dimensions et leurs marges. Publications de l’Institut Statistique de l’université de Paris, vol. 8, pp. 229–231. Paris (1959)Google Scholar
  18. 18.
    Fisher, N.I., Switzer, P.: Chi-plots of assessing of dependence. Biometrika 72, 253–265 (1985)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Fisher, N.I., Switzer, P.: Graphical assessment of dependence: is a picture worth 100 tests. Am. Stat. 55(3), 233–239 (2001)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Genest, C., Boies, J.C.: Detecting dependence with kendall plots. Am. Stat. 57(4), 275–284 (2003)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Deheuvels, P.: La fonction de dépendance empirique et ses propriétés. Un test non paramétrique d’indépendance. Acad. Roy. Belg. Bull. Cl. Sci. (5) 65(6), 274–292 (1979)Google Scholar
  22. 22.
    Genest, C., Rémillard, B., Beaudoin, D.: Goodness-of-fit tests for copulas: a review and a power study. Ins. Math. Econ. 44, 199–214 (2009)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Patton, A.J.: A review of copula models for economic time series. J. Multivariate Anal. 110, 4–18 (2012)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Box, G.E.P., Jenkins, G.M.: Time Series Analysis Forecasting and Control. Holden-Day, San Francisco (1976)zbMATHGoogle Scholar
  25. 25.
    Holt, C.C.: Forecasting Trends and Seasonal by Exponentially Weighted Averages. Office of Naval Research Memorandum, vol. 52 (1957)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Laila Ait Hassou
    • 1
  • Fadoua Badaoui
    • 2
    Email author
  • Okou Guei Cyrille
    • 3
  • Amine Amar
    • 4
  • Abdelhak Zoglat
    • 1
  • Elhadj Ezzahid
    • 5
  1. 1.Laboratoire de Mathématiques, Statistique et Applications, Faculté des SciencesCentre de Recherche Mathématiques de Rabat, Université Mohammed V de RabatRabatMorocco
  2. 2.Département Statistique, Démographie et ActuariatInstitut National de Statistique et d’Economie AppliquéeRabatMorocco
  3. 3.Unité de Formation et Recherche (UFR) EnvironnementUniversité Jean Lorougnon Guédé de DaloaDaloaCôte d’Ivoire
  4. 4.Moroccan Agency for Sustainable EnergyRabatMorocco
  5. 5.Faculty of Law and Economics, Laboratory of Applied EconomicsMohammed V University in RabatRabatMorocco

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