Is the Exchange Rate an Effective Anti-inflationary Policy Instrument?
AbstractThis paper aims at evaluating the performance of the so called ?hard currency policy? as an anti-inflationary weapon. The analysis takes place in the context of the Greek economy on the basis of a five-equation model including the behaviour of wages, import and export prices, the consumer price index as well as the GDP. The Simulation results indicate that the hard drachma policy is not adequate by itself as an inflation fighting device, unless it is accompanied by other anti-inflationary policies such as fiscal or incomes policy.
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Bibliographic InfoArticle provided by Cyprus Economic Society and University of Cyprus in its journal Ekonomia.
Volume (Year): 2 (1998)
Issue (Month): 1 (Summer)
Find related papers by JEL classification:
- F31 - International Economics - - International Finance - - - Foreign Exchange
- F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
- F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
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- Andreou, A. S. & Zombanakis, George A. & Likothanassis, S. D. & Georgakopoulos, E., 1998. "Modeling And Forecasting Exchange-Rate Shocks," MPRA Paper 51539, University Library of Munich, Germany, revised 06 Jun 1998.
- Andreou, Andreas S. & Zombanakis, George A. & Georgopoulos, E. F. & Likothanassis, S. D., 2000. "In Search of a Warning Strategy Against Exchange-rate Attacks: Forecasting Tactics Using Artificial Neural Networks," MPRA Paper 18197, University Library of Munich, Germany.
- Andreou, A. & Georgakopoulos, E. & Likothanassis, S. & Zombanakis, George A., 1998. "Testing Currency Predictability Using An Evolutionary Neural Network Model," MPRA Paper 51483, University Library of Munich, Germany, revised 24 Mar 1998.
- Andreou, Andreas S. & Zombanakis, George A. & Georgopoulos, E. F. & Likothanassis, S. D., 1998. "Forecasting Exchange-Rates via Local Approximation Methods and Neural Networks," MPRA Paper 17764, University Library of Munich, Germany.
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