Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2020 | 12 | nr 4 | 369--412
Tytuł artykułu

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

Treść / Zawartość
Warianty tytułu
Języki publikacji
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. (original abstract)
Opis fizyczny
  • Cracow University of Economics, Poland
  • Cracow University of Economics, Poland
  • Cracow University of Economics, Poland
  • [1] Alcaraz C., Claessens S., Cuadra G., Marques-Ibanez D., Sapriza H., (2019), Whatever it takes: what's the impact of a major nonconventional monetary policy intervention?, ECB Working Paper Series No. 2249.
  • [2] Alichi A., Benes J., Felman J., Feng I., Freedman C., Laxton D., Tanner E., Vavra D., Wang H., (2015), Adding the exchange rate as a tool to combat deflationary risks in the Czech Republic, IMF Working Paper No. WP/15/74.
  • [3] Arratibel O., Michaelis H., (2014), The impact of monetary policy and exchange rate shocks in Poland evidence from a time-varying VAR, ECB Working Paper Series No. 1636.
  • [4] Arias J. E., Rubio-Ramírez J. F., Waggoner D. F., (2018), Inference Based on Structural Vector Autoregressions Identified with Sign and Zero Restrictions: Theory and Applications, Econometrica 86(2), 685-720.
  • [5] Audzei V., Brázdik F., (2018), Exchange rate dynamics and their effect on macroeconomic volatility in selected CEE countries, Economic Systems 42, 584-596.
  • [6] Audzei V., Brázdik F., (2015), Monetary policy and exchange rate dynamics: The exchange rate as a shock absorber, Finance a úvěr-Czech Journal of Economics and Finance 65(5), 391-410.
  • [7] Baumeister C., Hamilton J. D., (2015), Sign restrictions, structural vector autoregressions, and useful prior information, Econometrica 83(5), 1963-1999.
  • [8] Baumeister C., Hamilton J. D., (2018), Inference in structural vector autoregressions when the identifying assumptions are not fully believed: Reevaluating the role of monetary policy in economic fluctuations, Journal of Monetary Economics 100, 48-65.
  • [9] Bertsche D., Braun R., (2020), Identification of structural vector autoregressions by stochastic volatility, Staff Working Paper No. 869, Bank of England.
  • [10] Borghijs A., Kuijs L., (2004), Exchange Rates in Central Europe: A Blessing or a Curse?, IMF Working Paper WP/04/2, 1-28.
  • [11] Caselli F., (2017), Did the exchange rate floor prevent deflation in the Czech Republic?, IMF Working Paper No. WP/17/206.
  • [12] Clarida R., Galí J., (1994), Sources of real exchange-rate fluctuations: How important are nominal shocks?, Carnegie-Rochester Conference Series on Public Policy 41, 1-56.
  • [13] Chen Y., Liu D., (2018), Dissecting real exchange rate fluctuations in China, Emerging Markets Finance & Trade 54, 288-Â-306.
  • [14] Dąbrowski M. A., (2012), Exchange rate regimes and output variability in Central European countries, Actual Problems of Economics 2(10), 80-91.
  • [15] Dąbrowski M. A., Kwiatkowski Ł., Wróblewska J., (2018), Sources of real exchange rate variability in Poland - Evidence from a Bayesian SVAR model with Markov Switching Heteroscedasticity, [in:] The 12th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, Conference Proceedings, [eds.:] Papież M., Śmiech S., Cracow: Foundation of the Cracow University of Economics, 90-99.
  • [16] Dąbrowski M. A., Wróblewska J., (2016), Exchange rate as a shock absorber in Poland and Slovakia: Evidence from Bayesian SVAR models with common serial correlation, Economic Modelling 58, 249-262.
  • [17] Egert B., Drine I., Lommatzsch K., Rault C., (2003), The Balassa-Samuelson effect in Central and Eastern Europe: myth or reality?, Journal of Comparative Economics 31(3), 552-572.
  • [18] Eichenbaum M. S., Johannsen B. K., Rebelo T. S., (2020), Monetary policy and the predictability of nominal exchange rates, Review of Economic Studies, doi: 10.1093/restud/rdaa002.
  • [19] Engel C., West K. D., (2006), Taylor rules and the Deutschmark-dollar real exchange rate, Journal of Money, Credit, and Banking 38(5), 1175-1194.
  • [20] Evenett S. J., Fritz J., (2016), Global Trade Plateaus: The 19th Global Trade Alert Report, London: CEPR Press.
  • [21] Farrant K., Peersman G., (2006), Is the exchange rate a shock absorber or source of shocks? New empirical evidence, Journal of Money, Credit and Banking 38(4), 939-961.
  • [22] Faust J., Leeper E. M., (1997), When Do Long-Run Identifying Restrictions Give Reliable Results?, Journal of Business & Economic Statistics 15(3), 345-353.
  • [23] Fidrmuc J., Wörgötter A., (2013), Slovakia: The consequences of joining the euro area before the crisis for a small catching-up economy, CESifo Forum 14(1), 57-63.
  • [24] Galí J., (2015), Monetary policy, inflation, and the business cycle: An introduction to the new Keynesian framework and its applications, Princeton and Oxford: Princeton University Press.
  • [25] Galí J., Monacelli T., (2005), Monetary policy and exchange rate volatility in a small open economy, Review of Economic Studies 72, 707-734.
  • [26] Gehrke B., Yao F., (2017), Are supply shocks important for real exchange rates? A fresh view from the frequency-domain, Journal of International Money and Finance 79, 99-114.
  • [27] Hamilton J. D., (2018), Why you should never use the Hodrick-Prescott filter. Review of Economics and Statistics 100(5), 831-843.
  • [28] Herwartz H., Lütkepohl H., (2014), Structural vector autoregressions with Markov switching: Combining conventional with statistical identification of shocks, Journal of Econometrics 183(1), 104-116.
  • [29] Inoue A., Kilian L., (2013), Inference on impulse response functions in structural VAR models, Journal of Econometrics 177(1), 1-13.
  • [30] Inoue A., Kilian L., (2019), Corrigendum to "Inference on impulse response functions in structural VAR models" [J. Econometrics 177 (2013), 1-13], Journal of Econometrics, 209(1), 139-143.
  • [31] Juvenal L., (2011), Sources of exchange rate fluctuations: Are they real or nominal?, Journal of International Money and Finance 30, 849-876.
  • [32] Kilian L., Lütkepohl H., (2017), Structural vector autoregressive analysis, Cambridge University Press.
  • [33] Krugman P., (2011), Exchange rates and price stickiness (wonkish), http://, access 02.06.2020.
  • [34] Kulikov D., Netšunajev A. (2013), Identifying monetary policy shocks via heteroskedasticity: a Bayesian approach, Bank of Estonia Working Papers WP2013-9, Bank of Estonia.
  • [35] Kupczyk R., (2018), Analiza sytuacji gospodarczej Słowacji po wejściu do unii walutowej, Studia Europejskie 2, 151-167.
  • [36] Kwiatkowski Ł., (2020), Bayesian VEC models with Markov-switching heteroscedasticity in forecasting macroeconomic time series, [in:] The 14th Proceedings of the Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, in print.
  • [37] Lanne M., Lütkepohl H., Maciejowska K., (2010), Structural vector autoregressions with Markov switching, Journal of Economic Dynamics and Control 34(2), 121-131.
  • [38] Lewis D. J., (2019), Identifying shocks via time-varying volatility, Staff Report No. 871, Federal Reserve Bank of New York.
  • [39] Lukacsy K., (2009), Price rigidity in Slovakia: Some facts and causes, Research In Economics And Business: Central And Eastern Europe 1(2), 5-26.
  • [40] Lütkepohl H., (2005), New introduction to multiple time series analysis, Springer Science & Business Media.
  • [41] Lütkepohl H., Netšunajev A., (2017), Structural vector autoregressions with heteroskedasticity: A review of different volatility models, Econometrics and Statistics 1, 2-18.
  • [42] Lütkepohl H., Woźniak T., (2020), Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity, Journal of Economic Dynamics & Control 113, 1-21.
  • [43] Mussa M., (1986), Nominal exchange rate regimes and the behavior of real exchange rates: Evidence and implications, Carnegie-Rochester Conference Series on Public Policy 25, 117-213.
  • [44] Osiewalski J., (2009), New Hybrid Models of Multivariate Volatility (a Bayesian Perspective). Przegląd Statystyczny (Statistical Review) 56(1), 15-22.
  • [45] Osiewalski J., Pajor A., (2009), Bayesian Analysis for Hybrid MSF-SBEKK Models of Multivariate Volatility, Central European Journal of Economic Modelling and Econometrics 1(2), 179-202.
  • [46] Pajor A., Wróblewska J., (2017), VEC-MSF models in Bayesian analysis of shortand long-run relationships, Studies in Nonlinear Dynamics & Econometrics 21(3), 1-22.
  • [47] Peersman G., (2011), The relative importance of symmetric and asymmetric shocks: The case of United Kingdom and euro area, Oxford Bulletin of Economics and Statistics 73(1), 104-118.
  • [48] Praet P., (2018), Maintaining price stability with unconventional monetary policy, sp180129.en.html, access: 20.02.2020.
  • [49] Rigobon R., (2003), Identification through Heteroskedasticity, The Review of Economics and Statistics 85(4), 777-792.
  • [50] Rogoff K., (1996), The purchasing power parity puzzle, Journal of Economic Literature 34, 647-668.
  • [51] Rose A. K., (2011), "Exchange Rate Regimes in the Modern Era": Fixed, floating, and flaky, Journal of Economic Literature 49(3), 652-672.
  • [52] Shevchuk V., (2014), Shock-absorbing properties of the exchange rates in transformation economies: SVAR estimates, [in:] Proceedings of the 8th Professor Aleksander Zelias International Conference on Modelling and Forecasting of Socio-Economic Phenomena, [eds.:] Papież M., Śmiech S., Cracow: Foundation of the Cracow University of Economics, 155-164.
  • [53] Sonora R., Tica J., (2014), Harrod, Balassa, and Samuelson (re)visit Eastern Europe, Journal Cogent Economics & Finance 2(1), 1-17.
  • [54] Stążka-Gawrysiak A., (2009), The shock-absorbing capacity of the flexible exchange rate in Poland, Focus on European Economic Integration 4, 54-70.
  • [55] Tian Y., Pentecost E. J., (2019), The changing sources of real exchange rate fluctuations in China, 1995-2017: Twinning the Western Industrial Economies?, The Chinese Economy 52(4), 358-376.
  • [56] Wajda-Lichy M., (2014), Traditional protectionism versus behind-the-border barriers in the post-crisis era: experience of three groups of countries: the EU, NAFTA and BRICS, Journal of International Studies 7(2), 141-151.
  • [57] Woźniak T., Droumaguet M., (2015), Assessing monetary policy models: Bayesian inference for heteroskedastic structural VARs, University of Melbourne Working Paper Series 2017.
  • [58] Wróblewska J., Pajor A., (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 11, 23-45.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.