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ANALYSIS OF THE MONETARY POLICY TRANSMISSION INTO CEEs COUNTRIES. A VAR APPROACH

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  • Patricia Amalia MERCEA (HANDRO)

    (University of Craiova, Romania)

Abstract

Understanding how real economy adjust to the exchange rate fluctuations enables us to anticipate the effects on inflation, capital market, exports, as well as the monetary policy responses. This study examines the extent of the exchange rate pass-through to the real economy (consumer price index, industrial production, capital market, exports, interest rate) in Bulgaria, Czech Republic, Poland, Romania, and Hungary over the 2008M01-2019M08 period. A Vector Autoregressive analysis using impulse-response functions supported the results for the short term and found a lower degree of passthrough for the exchange rate shocks for all CEE countries. The results of its econometric analysis show that the degree of the exchange rate pass-through is incomplete. The conclusion is that exchange rate remains an important instrument for monetary policy in these economies.

Suggested Citation

  • Patricia Amalia MERCEA (HANDRO), 2020. "ANALYSIS OF THE MONETARY POLICY TRANSMISSION INTO CEEs COUNTRIES. A VAR APPROACH," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 5(3), pages 90-102.
    • Handle: RePEc:brc:brccej:v:5:y:2020:i:3:p:90-102
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    1. Sebastian Edwards, 2006. "The Relationship Between Exchange Rates and Inflation Targeting Revisited," Working Papers Central Bank of Chile 409, Central Bank of Chile.
    2. Zsolt Darvas, 2013. "Monetary transmission in three central European economies: evidence from time-varying coefficient vector autoregressions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 40(2), pages 363-390, May.
    3. Frederic S. Miskin & Klaus Schmidt-Hebbel, 2007. "Does Inflation Targeting Make a Difference?," Central Banking, Analysis, and Economic Policies Book Series, in: Frederic S. Miskin & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Monetary Policy under Inflation Targeting, edition 1, volume 11, chapter 9, pages 291-372, Central Bank of Chile.
    4. 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.
    5. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    6. Marco Del Negro & Giorgio E. Primiceri, 2015. "Time Varying Structural Vector Autoregressions and Monetary Policy: A Corrigendum," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1342-1345.
    7. Jaromir Baxa & Tomas Sestorad, 2019. "The Czech Exchange Rate Floor: Depreciation without Inflation?," Working Papers 2019/1, Czech National Bank, Research and Statistics Department.
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    Keywords

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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • 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

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