IDEAS home Printed from https://ideas.repec.org/a/psc/journl/v12y2020i4p369-412.html
   My bibliography  Save this article

Sources of Real Exchange Rate Variability in Central and Eastern European Countries: Evidence from Structural Bayesian MSH-VAR Models

Author

Listed:
  • Marek A. Dąbrowski

    (Cracow University of Economics, Department of Macroeconomics)

  • Łukasz Kwiatkowski

    (Cracow University of Economics, Department of Econometrics and Operational Research)

  • Justyna Wróblewska

    (Cracow University of Economics, Department of Econometrics and Operational Research)

Abstract

This paper investigates the relative importance of cost, demand, financial and monetary shocks in driving real exchange rates in four CEE countries over 2000–2018. A two-country New Keynesian open economy model is used as a theoretical framework. In the empirical part, a Bayesian SVAR model with Markov switching heteroscedasticity is employed. The structural shocks are identified on the basis of volatility changes and named with reference to the sign restrictions derived from the economic model. Main findings are fourfold. First, real and financial shocks have similar contributions to real exchange variability, whereas that of monetary shocks is small. Second, financial shocks amplify exchange rate fluctuations stemming from real shocks. Third, even though the exchange rate gaps change over time, they remain quite similar across CEE countries except for Slovakia. Fourth, Slovakia introduced the euro at the time of a relatively large real overvaluation, which subsided after a lengthy adjustment process.

Suggested Citation

  • Marek A. Dąbrowski & Łukasz Kwiatkowski & Justyna Wróblewska, 2020. "Sources of Real Exchange Rate Variability in Central and Eastern European Countries: Evidence from Structural Bayesian MSH-VAR Models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 369-412, December.
  • Handle: RePEc:psc:journl:v:12:y:2020:i:4:p:369-412
    as

    Download full text from publisher

    File URL: http://cejeme.org/publishedarticles/2020-50-26-637420206596176439-9943.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Francesca Caselli, 2017. "Did the Exchange Rate Floor Prevent Deflation in the Czech Republic?," Review of Economics and Institutions, Università di Perugia, vol. 8(2).
    2. Baumeister, Christiane & Hamilton, James D., 2018. "Inference in structural vector autoregressions when the identifying assumptions are not fully believed: Re-evaluating the role of monetary policy in economic fluctuations," Journal of Monetary Economics, Elsevier, vol. 100(C), pages 48-65.
    3. Kenneth Rogoff, 1996. "The Purchasing Power Parity Puzzle," Journal of Economic Literature, American Economic Association, vol. 34(2), pages 647-668, June.
    4. Dominik Bertsche & Robin Braun, 2022. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 328-341, January.
    5. Juvenal, Luciana, 2011. "Sources of exchange rate fluctuations: Are they real or nominal?," Journal of International Money and Finance, Elsevier, vol. 30(5), pages 849-876, September.
    6. Andrew K. Rose, 2011. "Exchange Rate Regimes in the Modern Era : Fixed, Floating, and Flaky," Journal of Economic Literature, American Economic Association, vol. 49(3), pages 652-672, September.
    7. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
    8. Ali Alichi & Mr. Jaromir Benes & Mr. Joshua Felman & Irene Feng & Charles Freedman & Mr. Douglas Laxton & Mr. Evan C Tanner & David Vávra & Hou Wang, 2015. "Frontiers of Monetary Policymaking: Adding the Exchange Rate as a Tool to Combat Deflationary Risks in the Czech Republic," IMF Working Papers 2015/074, International Monetary Fund.
    9. Arratibel, Olga & Michaelis, Henrike, 2013. "The Impact of Monetary Policy and Exchange Rate Shocks in Poland: Evidence from a Time-Varying VAR," Discussion Papers in Economics 21088, University of Munich, Department of Economics.
    10. Jacek Osiewalski & Anna Pajor, 2009. "Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate Volatility," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 1(2), pages 179-202, November.
    11. Yong Chen & Dingming Liu, 2018. "Dissecting Real Exchange Rate Fluctuations in China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(2), pages 288-306, January.
    12. Audzei, Volha & Brázdik, František, 2018. "Exchange rate dynamics and their effect on macroeconomic volatility in selected CEE countries," Economic Systems, Elsevier, vol. 42(4), pages 584-596.
    13. Jarko Fidrmuc & Caroline Klein & Robert Price & Andreas Wörgötter, 2013. "Slovakia: A Catching Up Euro Area Member In and Out of the Crisis," OECD Economics Department Working Papers 1019, OECD Publishing.
    14. Clarida, Richard & Gali, Jordi, 1994. "Sources of real exchange-rate fluctuations: How important are nominal shocks?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 41(1), pages 1-56, December.
    15. Pajor Anna & Wróblewska Justyna, 2017. "VEC-MSF models in Bayesian analysis of short- and long-run relationships," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-22, June.
    16. repec:zbw:bofrdp:2018_014 is not listed on IDEAS
    17. Yuan Tian & Eric J. Pentecost, 2019. "The Changing Sources of Real Exchange Rate Fluctuations in China, 1995–2017: Twinning the Western Industrial Economies?," Chinese Economy, Taylor & Francis Journals, vol. 52(4), pages 358-376, July.
    18. Jordi Galí & Tommaso Monacelli, 2005. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 707-734.
    19. Lanne, Markku & Lütkepohl, Helmut & Maciejowska, Katarzyna, 2010. "Structural vector autoregressions with Markov switching," Journal of Economic Dynamics and Control, Elsevier, vol. 34(2), pages 121-131, February.
    20. Dmitry Kulikov & Aleksei Netsunajev, 2013. "Identifying monetary policy shocks via heteroskedasticity: a Bayesian approach," Bank of Estonia Working Papers wp2013-9, Bank of Estonia, revised 09 Dec 2013.
    21. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
    22. Egert, Balazs & Drine, Imed & Lommatzsch, Kirsten & Rault, Christophe, 2003. "The Balassa-Samuelson effect in Central and Eastern Europe: myth or reality?," Journal of Comparative Economics, Elsevier, vol. 31(3), pages 552-572, September.
    23. Jonas E. Arias & Juan F. Rubio‐Ramírez & Daniel F. Waggoner, 2018. "Inference Based on Structural Vector Autoregressions Identified With Sign and Zero Restrictions: Theory and Applications," Econometrica, Econometric Society, vol. 86(2), pages 685-720, March.
    24. Faust, Jon & Leeper, Eric M, 1997. "When Do Long-Run Identifying Restrictions Give Reliable Results?," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 345-353, July.
    25. Volha Audzei & Frantisek Brazdik, 2015. "Monetary Policy and Exchange Rate Dynamics: The Exchange Rate as a Shock Absorber," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(5), pages 391-410, October.
    26. Engel, Charles & West, Kenneth D., 2006. "Taylor Rules and the Deutschmark: Dollar Real Exchange Rate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1175-1194, August.
    27. Katarina Lukacsy, 2009. "Price Rigidity in Slovakia: Some Facts and Causes," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 1(2).
    28. Herwartz, Helmut & Lütkepohl, Helmut, 2014. "Structural vector autoregressions with Markov switching: Combining conventional with statistical identification of shocks," Journal of Econometrics, Elsevier, vol. 183(1), pages 104-116.
    29. Gert Peersman, 2011. "The Relative Importance of Symmetric and Asymmetric Shocks: The Case of United Kingdom and Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(1), pages 104-118, February.
    30. Daniel J Lewis, 2021. "Identifying Shocks via Time-Varying Volatility [First Order Autoregressive Processes and Strong Mixing]," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 88(6), pages 3086-3124.
    31. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575.
    32. Baumeister, Christiane & Hamilton, James, 2018. "Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role," CEPR Discussion Papers 12911, C.E.P.R. Discussion Papers.
    33. Christiane Baumeister & James D. Hamilton, 2015. "Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information," Econometrica, Econometric Society, vol. 83(5), pages 1963-1999, September.
    34. James D. Hamilton, 2018. "Why You Should Never Use the Hodrick-Prescott Filter," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 831-843, December.
    35. Carlo Alcaraz & Stijn Claessens & Gabriel Cuadra & David Marques-Ibanez & Horacio Sapriza, 2018. "Whatever it takes. What's the impact of a major nonconventional monetary policy intervention?," BIS Working Papers 749, Bank for International Settlements.
    36. Gehrke, Britta & Yao, Fang, 2017. "Are supply shocks important for real exchange rates? A fresh view from the frequency-domain," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 99-114.
    37. Louis Kuijs & Alain Borghijs, 2004. "Exchange Rates in Central Europe: A Blessing or a Curse?," IMF Working Papers 2004/002, International Monetary Fund.
    38. Roberto Rigobon, 2003. "Identification Through Heteroskedasticity," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 777-792, November.
    39. Mussa, Michael, 1986. "Nominal exchange rate regimes and the behavior of real exchange rates: Evidence and implications," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 25(1), pages 117-214, January.
    40. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
    41. Jarko Fidrmuc & Andreas Wörgötter, 2013. "Slovakia: The Consequences of Joining the Euro Aea before the Crisis for a Small Catching-up Economy," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 14(01), pages 57-63, May.
    42. Farrant, Katie & Peersman, Gert, 2006. "Is the Exchange Rate a Shock Absorber or a Source of Shocks? New Empirical Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(4), pages 939-961, June.
    Full references (including those not matched with items on IDEAS)

    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. Lütkepohl, Helmut & Woźniak, Tomasz, 2020. "Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    2. Dominik Bertsche & Robin Braun, 2022. "Identification of Structural Vector Autoregressions by Stochastic Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 328-341, January.
    3. Karamysheva, Madina & Skrobotov, Anton, 2022. "Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations," Journal of Economic Dynamics and Control, Elsevier, vol. 138(C).
    4. Dąbrowski, Marek A. & Papież, Monika & Śmiech, Sławomir, 2021. "Output volatility and exchange rates: New evidence from the updated de facto exchange rate regime classifications," MPRA Paper 107133, University Library of Munich, Germany.
    5. Atsushi Inoue & Lutz Kilian, 2020. "The Role of the Prior in Estimating VAR Models with Sign Restrictions," Working Papers 2030, Federal Reserve Bank of Dallas.
    6. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    7. Kilian, Lutz, 2022. "Facts and fiction in oil market modeling," Energy Economics, Elsevier, vol. 110(C).
    8. Fritsche, Jan Philipp & Klein, Mathias & Rieth, Malte, 2021. "Government spending multipliers in (un)certain times," Journal of Public Economics, Elsevier, vol. 203(C).
    9. Baumeister, Christiane & Hamilton, James D., 2020. "Drawing conclusions from structural vector autoregressions identified on the basis of sign restrictions," Journal of International Money and Finance, Elsevier, vol. 109(C).
    10. Braun, Robin, 2021. "The importance of supply and demand for oil prices: evidence from non-Gaussianity," Bank of England working papers 957, Bank of England.
    11. Carriero, Andrea & Clark, Todd E. & Marcellino, Massimiliano, 2021. "Using time-varying volatility for identification in Vector Autoregressions: An application to endogenous uncertainty," Journal of Econometrics, Elsevier, vol. 225(1), pages 47-73.
    12. Ilir Miteza & Altin Tanku & Ilir Vika, 2023. "Is the floating exchange rate a shock absorber in Albania? Evidence from SVAR models," Economic Change and Restructuring, Springer, vol. 56(2), pages 1297-1326, April.
    13. Agnieszka Stazka, 2006. "Sources of Real Exchange Rate Fluctuations in Central and Eastern Europe – Temporary or Permanent?," CESifo Working Paper Series 1876, CESifo.
    14. Helmut Herwartz & Alexander Lange & Simone Maxand, 2022. "Data‐driven identification in SVARs—When and how can statistical characteristics be used to unravel causal relationships?," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 668-693, April.
    15. Britta Gehrke & Fang Yao, 2016. "Persistence and volatility of real exchange rates: the role of supply shocks revisited," Reserve Bank of New Zealand Discussion Paper Series DP2016/02, Reserve Bank of New Zealand.
    16. Herwartz, Helmut & Lange, Alexander & Maxand, Simone, 2019. "Statistical identification in SVARs - Monte Carlo experiments and a comparative assessment of the role of economic uncertainties for the US business cycle," University of Göttingen Working Papers in Economics 375, University of Goettingen, Department of Economics.
    17. Robin Braun & Ralf Brüggemann, 2017. "Identification of SVAR Models by Combining Sign Restrictions With External Instruments," Working Paper Series of the Department of Economics, University of Konstanz 2017-07, Department of Economics, University of Konstanz.
    18. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models," CESifo Working Paper Series 5308, CESifo.
    19. Herwartz, Helmut & Wang, Shu, 2023. "Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    20. Inoue, Atsushi & Kilian, Lutz, 2022. "Joint Bayesian inference about impulse responses in VAR models," Journal of Econometrics, Elsevier, vol. 231(2), pages 457-476.

    More about this item

    Keywords

    open economy macroeconomics; real exchange rate; real and nominal shocks; Bayesian MS-VAR models; structural VAR models;
    All these keywords.

    JEL classification:

    • F33 - International Economics - - International Finance - - - International Monetary Arrangements and Institutions
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:psc:journl:v:12:y:2020:i:4:p:369-412. 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: Damian Jelito (email available below). General contact details of provider: http://cejeme.org/ .

    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.