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The Contribution of Observed and Unobserved Fundamentals to Exchange Rate Movements in Iran

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  • Eslamloueyan , Karim

    (Department of Economics, Shiraz University)

  • Yazdanpanah , Hamideh

    (Department of Economics, Shiraz University)

Abstract

Using a State-space model, this paper investigates the contribution of both observed and unobserved fundamentals to nominal exchange rate movement in Iran for the period 1991:2-2011:4. To this end, we follow Engel and West (2005) and Balke et al. (2013) and use an asset-pricing approach to develop a rational expectations present value exchange rate model. In order to examine the role of fundamental factors in exchange rate determination, we estimate the variance contribution of each factor to variance decomposition of the deviation of exchange rate from its long run equilibrium. The random walk Metropolis-Hastings algorithm, Kalman filter and Carter and Kohn algorithm are used to decompose the variance contributions. The results show that the observable fundamentals and the unobserved monetary demand shocks explain about 58.9 and 38.7 percentages of exchange rate fluctuation, respectively. Hence, contrary to previous studies in Iran, which have focused mainly on observable fundamental factors, we find that the unobservable fundamentals also play key role in determining the exchange rate movement in this country. Moreover, we find that the nominal exchange rate does not follow a near random walk behavior. It implies that the foreign exchange rate market in Iran is not efficient. Our findings might have important policy implications for monetary authorities.

Suggested Citation

  • Eslamloueyan , Karim & Yazdanpanah , Hamideh, 2013. "The Contribution of Observed and Unobserved Fundamentals to Exchange Rate Movements in Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(3), pages 89-115, July.
    • Handle: RePEc:mbr:jmonec:v:8:y:2013:i:3:p:89-115
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    References listed on IDEAS

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    1. Frankel, Jeffrey A & Froot, Kenneth A, 1987. "Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations," American Economic Review, American Economic Association, vol. 77(1), pages 133-153, March.
    2. Lui, Yu-Hon & Mole, David, 1998. "The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence," Journal of International Money and Finance, Elsevier, vol. 17(3), pages 535-545, June.
    3. Manzan, Sebastiano & Westerhoff, Frank H., 2007. "Heterogeneous expectations, exchange rate dynamics and predictability," Journal of Economic Behavior & Organization, Elsevier, vol. 64(1), pages 111-128, September.
    4. Cheung, Yin-Wong & Chinn, Menzie D. & Pascual, Antonio Garcia, 2005. "Empirical exchange rate models of the nineties: Are any fit to survive?," Journal of International Money and Finance, Elsevier, vol. 24(7), pages 1150-1175, November.
    5. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    6. Mark, Nelson C. & Sul, Donggyu, 2001. "Nominal exchange rates and monetary fundamentals: Evidence from a small post-Bretton woods panel," Journal of International Economics, Elsevier, vol. 53(1), pages 29-52, February.
    7. Ma, Yue & Kanas, Angelos, 2000. "Testing for a nonlinear relationship among fundamentals and exchange rates in the ERM," Journal of International Money and Finance, Elsevier, vol. 19(1), pages 135-152, February.
    8. Balke, Nathan S. & Ma, Jun & Wohar, Mark E., 2013. "The contribution of economic fundamentals to movements in exchange rates," Journal of International Economics, Elsevier, vol. 90(1), pages 1-16.
    9. Vygodina, Anna V. & Zorn, Thomas S. & DeFusco, Richard, 2008. "Asymmetry in the effects of economic fundamentals on rising and falling exchange rates," International Review of Financial Analysis, Elsevier, vol. 17(4), pages 728-746, September.
    10. Cerra, Valerie & Saxena, Sweta Chaman, 2010. "The monetary model strikes back: Evidence from the world," Journal of International Economics, Elsevier, vol. 81(2), pages 184-196, July.
    11. Junttila, Juha & Korhonen, Marko, 2011. "Nonlinearity and time-variation in the monetary model of exchange rates," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 288-302, June.
    12. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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    More about this item

    Keywords

    Nominal exchange rate; Observable fundamental factor; Unobservable fundamental factors; State-space model; Bayesian analysis;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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