Skip to main content

Advertisement

SpringerLink
Log in

What Can We Learn About the Real Exchange Rate Behavior in the Case of a Peripheral Country?

  • Original Article
  • Published:
Journal of Quantitative Economics Aims and scope Submit manuscript

Abstract

Since the reforms undertaken by policymakers to stop the depreciation of the Tunisian currency have failed, this paper investigates the dynamic of the Tunisian real exchange rate RER). The paper examines the nonlinear behavior of the power party purchase in Tunisia. It also considers whether the RER follows a true long-memory or spurious long-memory process with the presence of shifts. The analysis has two main findings. First, strong evidence of short memory in the presence of structural breaks appears in the Tunisian RER and, second, our results highlight that the presence of structural breaks creates distortions that prevent Tunisian policymakers from reacting to the exchange rate system effectively through central bank intervention. The dynamic of the Tunisian exchange rate is governed by the heterogeneity among investors and policy changes. The presence of multiple regimes in the Tunisian exchange rate implies that monetary policy cannot affect the exchange rate dynamic through central bank interventions. Therefore, this study recommends that Tunisian policymakers follow a market-oriented strategy in making relevant reforms, such as revisiting the weight of the dinar against the euro, to ensure better management of the risks associated with foreign exchange fluctuations.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. We note that the Tunisian currency is anchored against the euro to within 80%.

  2. Other theories aim to explain the dynamics of exchange rates such as the balance of payments and financial globalization.

  3. Cheung and Lai (1994) and Rogoff (1996) explained the slow adjustment through inter-temporal smoothing or cross-country wealth distribution.

  4. The structure of fundamentals-based models is similar between studies.

  5. Extensive mathematical research over recent years has focused on important issues in economics and finance such as stock exchanges and foreign currency dynamics.

  6. Canada, Germany, the United Kingdom, France, Italy, Japan, Austria, Belgium, Denmark, the Netherlands, Norway, Sweden, Switzerland, Finland, Greece, Portugal, and Spain.

  7. Under the assumption of spatially separated countries and significant shipping costs.

  8. To discriminate between different models, the authors used out-of-sample forecasting behavior and employed the mean squared error to distinguish between out-of-sample forecasting and sample forecasts.

  9. The major currencies are the Canadian dollar, Japanese Yen, Swiss Franc, Singapore dollar, and the British pound. The less liquid currencies are: Indonesia, South Korea, Malaysia, Philippines, and Thailand.

  10. In this analysis, our objective is not to address all tests used in the literature to detect long memory or structural breaks; we retain the main tests used in existing studies.

  11. For consistency and asymptotic normality see assumptions (1–5) and (10–50) in Shimotsu and Phillips (2005), pp. 1893–1897.

  12. The code is available on the Perron home page: http://people.bu.edu/perron/.

  13. A commando army was formed by dozens of men who were conscripted in Libya. This act caused France, the United States, and Morocco to send warships and planes to suppress the insurgency. In response to Libyan involvement, Tunisian President Bourguiba cancelled diplomatic relations with Libya.

  14. The devaluation of the dinar reached a nominal level of 45% and a real level of 25% in 1988.

  15. Here, we select ESTAR models among various threshold models such as SETAR and TAR. Our motivation behind this choice is that the exchange rate dynamic typically occurs smoothly because it depends on the fundamentals. Furthermore, this model is the most used in previous literature.

References

  • Agiakloglou, Christos, Paul Newbold, and Mark Wohar. 1992. Bias in an estimator of the fractional difference Parameter. Journal of Time Series Analysis 13: 235–246.

    Article  Google Scholar 

  • Aloy, Marcel, Mohamed Boutahar, Karine Gente, and Anne Péguin-Feissolle. 2011. Purchasing power parity and the long-memory properties of real exchange rates: Does one size fit all? Economic Modelling 28: 1279–1290.

    Article  Google Scholar 

  • Andrews, Donald W.K., and Patrik Guggenberger. 2003. A bias-reduced log-periodogram regression estimator for the long-memory parameter. Econometrica 71: 675–712.

    Article  Google Scholar 

  • Bai, Jushan, and Pierre Perron. 1998. Estimating and testing linear models with multiple structural changes. Econometrica 66: 47–78.

    Article  Google Scholar 

  • Bai, Jushan, and Pierre Perron. 2003. Computation and analysis of multiple structural change models. Journal of Applied Econometrics 18: 1–22.

    Article  Google Scholar 

  • Banerjee, Anindya, and Giovanni Urga. 2005. Modelling structural breaks, long-memory, and stock market volatility: An overview. Journal of Econometrics 129: 1–34.

    Article  Google Scholar 

  • Barkoulas, John T., Anthony G. Barilla, and William Wells. 2016. Long-memory exchange rate dynamics in the euro era. Chaos, Solitons and Fractals 86: 92–100.

    Article  Google Scholar 

  • Baum, Christopher F., John T. Barkoulas, and Mustafa Caglayan. 1999. Long-memory or structural breaks: Can either explain nonstationary real exchange rates under the current float? Journal of International Financial Markets, Institutions and Money 9: 359–376.

    Article  Google Scholar 

  • Beckmann, Joscha. 2013. Nonlinear adjustment, purchasing power parity and the role of nominal exchange rates and prices. North American Journal of Economics and Finance 24: 176–190.

    Article  Google Scholar 

  • Benninga, Simon, and Aris Protopapadakis. 1988. The equilibrium pricing of exchange rates and assets when trade takes time. Journal of International Economics 7: 129–49.

    Google Scholar 

  • Beran, Jan. 1994. Statistics for long-memory processes. New York: Chapman and Hall.

    Google Scholar 

  • Bergman, U.Michael, and Jesper Hansson. 2005. Real exchange rates and switching regimes. Journal of International Money and Finance 24: 121–138.

    Article  Google Scholar 

  • Berkes, István, Lajos Horvath, Kokoszka Piotr, and Qi-Man Shao. 2006. On discriminating between long-range dependence and changes in mean. Annals of Statistics 34: 1140–1165.

    Article  Google Scholar 

  • Brown, Robert L., James Durbin, and James M. Evans. 1975. Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society, Series B 37: 149–192.

    Google Scholar 

  • Caporale, Guglielmo Maria, and Luis A. Gil-Alana. 2013. Long memory and fractional integration in high frequency data on the US dollar/British pound spot exchange rate. International Review of Financial Analysis 29: 1–9.

    Article  Google Scholar 

  • Cheung, Yin-Wong, and Kon S. Lai. 1994. Mean reversion in real exchange rates. Economics Letters 46: 251–256.

    Article  Google Scholar 

  • Kyongwook, Choi, and Eric Zivot. 2007. Long memory and structural changes in the forward discount: An empirical investigation. Journal of International Money and Finance 26 (3): 342–363.

    Article  Google Scholar 

  • Chow, Gregory C. 1960. Test of equality between sets of coefficients in tow linear regressions. Econometrica 28: 591–603.

    Article  Google Scholar 

  • Crato, Nuno, and Bonnie K. Ray. 2000. Memory in returns and volatilities of future’s contracts. Journal of Futures Markets 20: 525–543.

    Article  Google Scholar 

  • De Grauwe, Paul, and Marianna Grimaldi. 2001. Exchange rates, prices and money: A long run perspective. International Journal of Finance and Economics 6: 289–314.

    Article  Google Scholar 

  • Dewachter, Hans. 2001. Can Markov switching models replicate chartist profits in the foreign exchange market? Journal of International Money and Finance 20: 25–41.

    Article  Google Scholar 

  • Diebold, Francis X., and Atsushi Inoue. 2001. Long memory and regime switching. Journal of Econometrics 105: 131–159.

    Article  Google Scholar 

  • Dufrénot, Gilles, Laurent Mathieu, Valerie Mignon, and Anne Peguin-Feissolle. 2006. Persistent misalignments of the European exchange rates: Some evidence from non-linear cointegration. Applied Economics 38: 203–229.

    Article  Google Scholar 

  • Dufrénot, Gilles, Sandrine Lardic, Laurent Mathieu, Valerie Mignon, and Anne Peguin-Feissolle. 2008. Explaining the European exchange rates deviations: Long memory or non-linear adjustment? Journal International Financial Markets, Institutions and Money 18: 207–215.

    Article  Google Scholar 

  • Dumas, Bernard. 1992. Dynamic equilibrium and the real exchange rate in a spatially separated world. The Review of Financial Studies 5: 153–180.

    Article  Google Scholar 

  • Elliott, Graham, Thomas J. Rothenberg, and James H. Stock. 1996. Efficient tests for an autoregressive unit root. Econometrica 64: 813–836.

    Article  Google Scholar 

  • Engel, Charles. 1994. Can the Markov switching model forecast exchange rates? Journal of International Economics 36: 151–165.

    Article  Google Scholar 

  • Evans, Martin D.D., and Karen Lewis. 1995. Do long-term swings in the dollar affect estimates of the risk premia? Review of Financial Studies 8: 709–742.

    Article  Google Scholar 

  • Flood, Robert P., and Andrew K. Rose. 1999. Understanding exchange rate volatility without the contrivance of macroeconomics. The Economic Journal 109: 660–672.

    Article  Google Scholar 

  • Froot, Kenneth A., and Rogoff Kenneth. 1995. Perspective on PPA and long-run real exchange rates. In Handbook of international economics, ed. Rogoff Kenneth, and Grossman Gene. Amsterdam: North Holland.

    Google Scholar 

  • Geweke, John, and Susan Porter-Hudak. 1983. The estimation and application of long memory time series models. Journal of Time Series Analysis 4: 221–238.

    Article  Google Scholar 

  • Granger, Clive W.J., and R. Roselyne Joyeux. 1980. An introduction to long memory time series models and fractional differencing. Journal of Time Series Analysis 1: 15–39.

    Article  Google Scholar 

  • Granger Clive, W.J., and Namwon Hyung. 2004. Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns. Journal of Empirical Finance 11: 399–421.

    Article  Google Scholar 

  • Hamilton, James D. 1989. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica 57: 357–384.

    Article  Google Scholar 

  • Hanna, K.E.D. 2001. Competitiveness in the MENA region: Egypt, Morocco, Tunisia, Turkey. In Seconde conférence du FEMISE, Marseille. March 29 and 30, 9.

  • Hansen, B. 2001. The new econometrics of structural changes: Understanding and dating changes in US productivity. mimeo, University of Wisconsin.

  • Henry, Marc. 2001. Robust automatic bandwidth for long memory. Journal of Time Series Analysis 22: 293–316.

    Article  Google Scholar 

  • Hosking, Jonathan R.M. 1981. Fractional differencing. Biometrica 68: 165–176.

    Article  Google Scholar 

  • Hurvich, Clifford M., Rohit Deo, and Brodsky Julia. 1998. The mean squared error of Geweke and Porter-Hudak’s estimator of the memory parameter of a long memory time series. Journal of Time Series 19: 19–46.

    Article  Google Scholar 

  • Imbs, Jean, Haroon Mumtaz, Morten O. Ravn, and Helene Rey. 2005. PPP strikes back: Aggregation and the real exchange rate. The Quarterly Journal of Economics 120: 1–43.

    Google Scholar 

  • Juselius, Katarina, and R. Ronald MacDonald. 2004. International parity relationships between the USA and Japan. Japan and the World Economy 16: 17–34.

    Article  Google Scholar 

  • Kilian, Lutz, and Mark P. Taylor. 2003. Why is it so difficult to beat the random walk forecast of exchange rates. Journal of International Economics 60: 85–107.

    Article  Google Scholar 

  • Krugman, Paul R. 1991. Target zones and exchange rate dynamics. Quarterly Journal of Economics 106: 669–682.

    Article  Google Scholar 

  • Lamoureux, Christopher G., and William D. Lastrapes. 1990. Heteroskedasticity in stock returns data: Volume versus GARCH effects. Journal of Finance 45: 221–229.

    Article  Google Scholar 

  • Lee, Hsiu-Yun, and Show-Lin Chen. 2006. Why use Markov-switching models in exchange rate prediction? Economic Modelling 23: 662–668.

    Article  Google Scholar 

  • Maican, Florin G., and Richard J. Sweeney. 2013. Real exchange rate adjustment in European transition countries. Journal of Banking and Finance 37: 907–926.

    Article  Google Scholar 

  • Meese, Richard A., and Kenneth Rogoff. 1983. Empirical exchange rate models of the seventies: Do they fit out of sample? Journal of International Economics 14: 3–24.

    Article  Google Scholar 

  • Menkhoff, Lukas, and Mark P. Taylor. 2007. The obstinate passion of foreign exchange professionals: Technical analysis. Journal of Economic Literature 45: 936–972.

    Article  Google Scholar 

  • Mensi, Walid, Shawkat Hammoudeh, and Seong-Min Yoon. 2014. Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements. International Review of Economics and Finance 30: 101–119.

    Article  Google Scholar 

  • Michael, P., A. Robert Nobay, and David A. Peel. 1997. Transaction costs and nonlinear adjustment in real exchange rates: An empirical investigation. Journal of Political Economy 105: 862–878.

    Article  Google Scholar 

  • Nam, Deokwoo. 2011. The roles of nominal exchange rate and relative price adjustments in PPP reversion. Journal of Money Credit and Banking 43: 775–785.

    Article  Google Scholar 

  • Ng, S., and P. Perron. 1995. Unit Root Tests in ARMA Models with Data-Dependent Methods for the Selection of the Truncation Lag. Journal of the American Statistical Association 90: 268–281.

    Article  Google Scholar 

  • Nikolsko-Rzhevsky, Alex, and Ruxandra Prodan. 2012. Markov switching and exchange rate predictability. International Journal of Forecasting 28: 353–365.

    Article  Google Scholar 

  • Ohanissian, Arek, Jeffrey R. Russell, and Ruey S. Tsay. 2008. True or spurious long memory? A new test. Journal of Business and Economics Statistics 26: 161–175.

    Article  Google Scholar 

  • Perron, Pierre. 1989. The great crash, the oil price schock, and the unit root hypothesis. Econometrica 57 (6): 1361–1401.

    Article  Google Scholar 

  • Perron, Pierre. 1990. Testing for a unit root in a time series regression with a changing mean. Journal of Business & Economic Statistics 8: 153–162.

    Google Scholar 

  • Perron, Pierre, and Zhongjun, Qu. 2004. An analytical evaluation of the log-periodogram estimate in the presence of level shifts and its implications for stock returns volatility. Working Paper, No. 16, Boston University.

  • Perron, Pierre, and Qu Zhongjun. 2010. Long-memory and level shifts in the volatility of stock market return indices. Journal of Business & Economic Statistics 28: 275–290.

    Article  Google Scholar 

  • Reitz, Stefan, and Mark P. Taylor. 2008. The coordination channel of foreign exchange intervention: A nonlinear microstructural analysis. European Economic Review 52: 55–76.

    Article  Google Scholar 

  • Robinson, P.M. 1995. Log-periodogram regression of time series with long range dependence. Annals of Statistics 23: 1048–1072.

    Article  Google Scholar 

  • Rogoff, Kenneth. 1996. The purchasing power parity puzzle. Journal of Economic Literature 34: 647–668.

    Google Scholar 

  • Shimotsu, Katsumi. 2006. Exact local Whittle estimation of fractional integration with unknown mean and time trend. Working Paper No. 1061, Queen’s University, Canada.

  • Sarno, Lucio, and Mark P. Taylor. 2002. Purchasing power parity and the real exchange rate. International Monetary Fund Staff Papers 49: 65–105.

    Google Scholar 

  • Shimotsu, Katsumi, and Peter C.B. Phillips. 2004. Local Whittle estimation in non-stationary and unit root cases. Annals of Statistics 32: 656–692.

    Article  Google Scholar 

  • Shimotsu, Katsumi, and Peter C.B. Phillips. 2005. Exact local Whittle estimation of fractional integration. Annals of Statistics 33: 1890–1933.

    Article  Google Scholar 

  • Smith, Aaron. 2005. Level shifts and the illusion of long memory in economic time series. Journal of Business & Economic Statistics 23: 321–335.

    Article  Google Scholar 

  • Soofi, Abdol S., Shouyang Wang, and Yugin Zhang. 2006. Testing for long memory in the Asian foreign exchange rates. Journal of Systems Science and Complexity 19: 182–190.

    Article  Google Scholar 

  • Taylor, Alan M. 2001. Potential pitfalls for the purchasing-power parity puzzle: Sampling and specification biases in mean-reversion tests of the low of one price. Econometrica 69: 473–498.

    Article  Google Scholar 

  • Taylor, Alan M., and Mark P. Taylor. 2004. The purchasing power parity debate. NBER Working Paper, No. 10607.

  • Taylor, Mark P. 2006. Real exchange rates and purchasing power parity: Mean-reversion in economic thought. Applied Financial Economics 16: 1–17.

    Article  Google Scholar 

  • Taylor, Mark P., David A. Peel, and Lucio Sarno. 2001. Nonlinear mean-reversion in real exchange rates: Towards a solution to the purchasing parity puzzles. International Economic Review 42: 1015–1042.

    Article  Google Scholar 

  • Teräsvirta, Timo. 1994. Specification, estimation and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89: 208–218.

    Google Scholar 

  • Wali, Muammer, Felix Chan, and Meher Manzur. 2017. Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies? Journal of Asian Economics 50: 62–72.

    Article  Google Scholar 

  • Wu, Jyh-Lin, and Hu Yu-Hau. 2009. New evidence on nominal exchange rate predictability. Journal of International Money and Finance 28: 1045–1063.

    Article  Google Scholar 

  • Zivot, Eric, and Donald W.K. Andrews. 1992. Further evidence on the great crash, the oil price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics 10 (3): 251–270.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. EDC Paris Business School, OCRE-Laboratory, 70 Galeries des Damiers, Paris la Défense 1, Courbevoie cedex, 92415, France

    Zied Ftiti

  2. University of Tunis, ISG Tunis, LR GEF-2A, 1002, Le Bardo, Tunisia

    Zied Ftiti

  3. University of Tunis, ISG Tunis, UR UAQUAP, 1002, Le Bardo, Tunisia

    Slim Chaouachi

Authors
  1. Zied Ftiti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Slim Chaouachi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zied Ftiti.

Additional information

We are grateful to editors Professor Dilip N. Nachane and Professor Bernhard Herz. We would to thank two reviewers for their helpful comments and recommendations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ftiti, Z., Chaouachi, S. What Can We Learn About the Real Exchange Rate Behavior in the Case of a Peripheral Country?. J. Quant. Econ. 16, 681–707 (2018). https://doi.org/10.1007/s40953-017-0098-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40953-017-0098-z

Keywords

JEL Classification

Search

Navigation