Rational Speculative Bubbles in Iran Informal Exchange Rate and Currency Crisis: Time-varying probabilities Markov regime switching approach - Ali Tayebnia (Faslnāmah-i Pizhūhish/Nāmah-i Iqtisādī, 2019)
The purpose of this paper is identifying speculative rational bubbles and applying early warning indices to illustrate these bubbles in USD/IRR informal exchange rate during volatile period of March 2011 to September 2018. The deviation of the exchange rate from fundamental values which is known as bubble may occur as a result of a speculative attack to the value of local currency which, if the authorities do not defend the value of the national currency, will lead to a currency crisis. Therefore, it is very important for policy-makers to correctly identify bubble periods to intervene timely in the foreign exchange market and to prevent deviation of exchange rate from its fundamental value. For this purpose, rational speculative bubbles modeling using Markov regime-switching model with time-varying probabilities including dormant, collapsing and explosive regimes with high ability in identifying the time of formation and collapsing of bubbles has been done. In our model, the sanction index and changes in foreign exchange reserves are early warning indicators. The sanction index is the cause of speculative demand in the informal foreign exchange market over the period covered by this study which, coupled with central bank interventions to reduce the pressure on the foreign exchange market, have been able to explain recent currency speculative bubbles. Our results confirm that rational speculative bubbles exist in USD/IRR informal exchange rate. Based on our results, time intervals identified as explosive regime are exactly contemporaneous with currency crisis periods. On the other hand, collapsing regimes tend to coincide with post-crisis periods. Dormant regimes identified in this study correspond to periods that the exchange rate return has a mild increasing trend. Comparing designed model to other specifications display sufficient robustness in the presented model.