Modeling Real Exchange Rate in Iran using Markov Switching Autoregressive Model
This study tries to model real exchange rate using a two-state Markov autoregressive model. The empirical results indicate that the real exchange rate cycles are well explained by a switching autoregressive pattern rather than a simple autoregressive model. The Markov switching autoregressive model...
| Main Authors: | , |
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| Format: | Article |
| Language: | fas |
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Tarbiat Modares University
2014-05-01
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| Series: | پژوهشهای اقتصادی |
| Subjects: | |
| Online Access: | http://ecor.modares.ac.ir/article-18-9871-en.pdf |
| Summary: | This study tries to model real exchange rate using a two-state Markov autoregressive model. The empirical results indicate that the real exchange rate cycles are well explained by a switching autoregressive pattern rather than a simple autoregressive model. The Markov switching autoregressive model (MSAR) is a non-linear method, which models volatility in financial markets well and identifies periods of regime change of exchange rate volatility. The results show that duration of staying in high volatility regime (regime 1) is less than that of low volatility regime (regime 2) in Iran. The other result is the possibility of testing for the purchasing power parity (PPP) theory, implying that existence a regular trend in data and lack of convergence potential real exchange rate to 1 leads to reject the PPP theory. Since there is a regular trend in real exchange rate data, we can reject the PPP theory in Iran. This also indicates that the real variables affect real exchange rate only in the long-run. |
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| ISSN: | 1735-6768 2980-7832 |