IDEAS home Printed from https://ideas.repec.org/a/mes/emfitr/v47y2011i4p49-58.html
   My bibliography  Save this article

Drivers of Exchange Rate Dynamics in Selected CIS Countries: Evidence from a Factor-Augmented Vector Autoregressive (FAVAR) Analysis

Author

Listed:
  • Christian Dreger
  • Jarko Fidrmuc

Abstract

We investigate the likely sources of exchange rate dynamics in selected member countries of the Commonwealth of Independent States (CIS; Russia, Kazakhstan, Ukraine, Kyrgyzstan, Azerbaijan, and Moldova) over the past decade (1999-2010). Evidence is based on country VARs augmented by a regional common-factor structure (FAVAR model). The models include nominal exchange rates, the common factor of exchange rates in the CIS countries, and international drivers such as global trade, share prices, and oil price. Global, regional, and idiosyncratic shocks are identified in a standard Cholesky fashion. Their relevance for exchange rates is explored by a decomposition of the variance of forecast errors. The impact of global shocks on the development of exchange rates has increased, particularly if financial shocks are considered. Because of the recent global financial crisis, regional shocks have become more important at the expense of global shocks.

Suggested Citation

  • Christian Dreger & Jarko Fidrmuc, 2011. "Drivers of Exchange Rate Dynamics in Selected CIS Countries: Evidence from a Factor-Augmented Vector Autoregressive (FAVAR) Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(4), pages 49-58, July.
    • Handle: RePEc:mes:emfitr:v:47:y:2011:i:4:p:49-58
    as

    Download full text from publisher

    File URL: http://mesharpe.metapress.com/link.asp?target=contribution&id=0647560HT2458955
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Egert, Balazs, 2005. "Equilibrium exchange rates in South Eastern Europe, Russia, Ukraine and Turkey: Healthy or (Dutch) diseased?," Economic Systems, Elsevier, vol. 29(2), pages 205-241, June.
    2. Jan Fidrmuc & Jarko Fidrmuc, 2003. "Disintegration and Trade," Review of International Economics, Wiley Blackwell, vol. 11(5), pages 811-829, November.
    3. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    4. Balazs Egert & Carol Leonard, 2008. "Dutch Disease Scare in Kazakhstan: Is it real?," Open Economies Review, Springer, vol. 19(2), pages 147-165, April.
    5. Schnabl, Gunther, 2005. "International capital markets and exchange rate stabilization in the CIS," Journal of Comparative Economics, Elsevier, vol. 33(3), pages 425-440, September.
    6. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    7. Kutan, Ali M. & Wyzan, Michael L., 2005. "Explaining the real exchange rate in Kazakhstan, 1996-2003: Is Kazakhstan vulnerable to the Dutch disease?," Economic Systems, Elsevier, vol. 29(2), pages 242-255, June.
    8. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(1), pages 387-422.
    9. James H. Stock & Mark W. Watson, 2005. "Understanding Changes In International Business Cycle Dynamics," Journal of the European Economic Association, MIT Press, vol. 3(5), pages 968-1006, September.
    10. Lommatzsch, Kirsten & Tober, Silke, 2004. "What is behind the real appreciation of the accession countries' currencies?: An investigation of the PPI-based real exchange rate," Economic Systems, Elsevier, vol. 28(4), pages 383-403, December.
    11. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-144, January.
    12. Ronald MacDonald & Cezary Wojcik, 2008. "Productivity, Demand, and Regulated Price Effects Revisited: An Analysis of the Real Bilateral Exchange Rates of Four New EU Member States," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 44(3), pages 48-65, May.
    13. Andrei Shleifer & Daniel Treisman, 2005. "A Normal Country: Russia After Communism," Journal of Economic Perspectives, American Economic Association, vol. 19(1), pages 151-174, Winter.
    14. Vladimir Chaplygin & Andrew Hughes Hallett & Christian Richter, 2006. "Monetary integration in the ex‐Soviet Union: A ‘union of four’?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 14(1), pages 47-68, March.
    15. Gunther Schnabl, 2004. "International Capital Markets, Macroeconomic Stability, and Exchange Rate Stabilization in the CIS and East Asia," International Finance 0410009, University Library of Munich, Germany, revised 01 Mar 2005.
    16. repec:zbw:bofitp:2007_007 is not listed on IDEAS
    17. repec:zbw:bofitp:2009_006 is not listed on IDEAS
    18. repec:zbw:bofitp:2007_016 is not listed on IDEAS
    19. Ms. Katerina Kalcheva & Nienke Oomes, 2007. "Diagnosing Dutch Disease: Does Russia Have the Symptoms?," IMF Working Papers 2007/102, International Monetary Fund.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    2. Dreger, Christian & Kholodilin, Konstantin A. & Ulbricht, Dirk & Fidrmuc, Jarko, 2016. "Between the Hammer and the Anvil: The Impact of Economic Sanctions and Oil Prices on Russia’s Ruble," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 44(2), pages 295-308.
    3. Viktar Dudzich, 2022. "Real Exchange Rate Misalignments and Currency Crises in the Former Soviet Union Countries," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(3), pages 384-416, September.
    4. repec:zbw:bofitp:2018_017 is not listed on IDEAS
    5. Hyeyoen Kim & Doojin Ryu, 2013. "Forecasting Exchange Rate from Combination Taylor Rule Fundamental," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 81-92, September.
    6. Danglun Luo & Qianwei Ying, 2014. "Political Connections and Bank Lines of Credit," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(03), pages 5-21, May.
    7. Skorepa, Michal & Komarek, Lubos, 2015. "Sources of asymmetric shocks: The exchange rate or other culprits?," Economic Systems, Elsevier, vol. 39(4), pages 654-674.
    8. Oleksandr Faryna & Heli Simola, 2018. "The Transmission of International Shocks to CIS Economies: A Global VAR Approach," Working Papers 04/2018, National Bank of Ukraine.
    9. Faryna, Oleksandr & Simola, Heli, 2018. "The transmission of international shocks to CIS economies: A Global VAR approach," BOFIT Discussion Papers 17/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    10. Li, Kaifeng & Devpura, Neluka & Cheng, Sijia, 2022. "How did the oil price affect Japanese yen and other currencies? Fresh insights from the COVID-19 pandemic," Pacific-Basin Finance Journal, Elsevier, vol. 75(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christian Dreger & Jarko Fidrmuc, 2009. "Drivers of Exchange Rate Dynamics in Selected CIS Countries: Evidence from a FAVAR Analysis," Discussion Papers of DIW Berlin 867, DIW Berlin, German Institute for Economic Research.
    2. Yulia Vymyatnina, 2014. "Spillover Effects in the Customs Union of Russia, Kazakhstan and Belarus," EcoMod2014 7160, EcoMod.
    3. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
    4. Rangan Gupta & Alain Kabundi & Stephen Miller & Josine Uwilingiye, 2014. "Using large data sets to forecast sectoral employment," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(2), pages 229-264, June.
    5. Fakhri Hasanov, 2010. "The Impact of Real Oil Price on Real Effective Exchange Rate: The Case of Azerbaijan," Discussion Papers of DIW Berlin 1041, DIW Berlin, German Institute for Economic Research.
    6. Leif Anders Thorsrud, 2013. "Global and regional business cycles. Shocks and propagations," Working Paper 2013/08, Norges Bank.
    7. M. Ayhan Kose & Christopher Otrok & Eswar Prasad, 2012. "Global Business Cycles: Convergence Or Decoupling?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(2), pages 511-538, May.
    8. Shintani, Mototsugu & Guo, Zi-Yi, 2011. "Finite Sample Performance of Principal Components Estimators for Dynamic Factor Models: Asymptotic vs. Bootstrap Approximations," EconStor Preprints 167627, ZBW - Leibniz Information Centre for Economics.
    9. C. Glocker & G. Sestieri & P. Towbin, 2017. "Time-varying fiscal spending multipliers in the UK," Working papers 643, Banque de France.
    10. Bagliano, Fabio C. & Morana, Claudio, 2009. "International macroeconomic dynamics: A factor vector autoregressive approach," Economic Modelling, Elsevier, vol. 26(2), pages 432-444, March.
    11. Lombardi, Marco J. & Godbout, Claudia, 2012. "Short-term forecasting of the Japanese economy using factor models," Working Paper Series 1428, European Central Bank.
    12. repec:cte:wsrepe:23974 is not listed on IDEAS
    13. Davide Brignone & Alessandro Franconi & Marco Mazzali, 2023. "Robust Impulse Responses using External Instruments: the Role of Information," Papers 2307.06145, arXiv.org.
    14. Girardin, Eric & Moussa, Zakaria, 2011. "Quantitative easing works: Lessons from the unique experience in Japan 2001â2006," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(4), pages 461-495, October.
    15. International Monetary Fund, 2013. "Republic of Kazakhstan: Selected Issues," IMF Staff Country Reports 2013/291, International Monetary Fund.
    16. Miao, Ke & Phillips, Peter C.B. & Su, Liangjun, 2023. "High-dimensional VARs with common factors," Journal of Econometrics, Elsevier, vol. 233(1), pages 155-183.
    17. Qin Zhang & He Ni & Hao Xu, 2023. "Forecasting models for the Chinese macroeconomy in a data‐rich environment: Evidence from large dimensional approximate factor models with mixed‐frequency data," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(1), pages 719-767, March.
    18. Beck, Guenter W. & Hubrich, Kirstin & Marcellino, Massimiliano, 2009. "On the importance of sectoral shocks for price-setting," CFS Working Paper Series 2009/32, Center for Financial Studies (CFS).
    19. Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021. "Macroeconomic data transformations matter," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
    20. Oskenbayev, Yessengali & Yilmaz, Mesut & Abdulla, Kanat, 2013. "Resource concentration, institutional quality and the natural resource curse," Economic Systems, Elsevier, vol. 37(2), pages 254-270.
    21. Fiorelli, Cristiana & Meliciani, Valentina, 2019. "Economic growth in the era of unconventional monetary instruments: A FAVAR approach," Journal of Macroeconomics, Elsevier, vol. 62(C).

    More about this item

    Keywords

    CIS countries; exchange rates; FAVAR models; financial crisis;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mes:emfitr:v:47:y:2011:i:4:p:49-58. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/MREE20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.