Econometrics
Mohammad Feghhi Kashani; Teymor Mohammadi; zahra Aghighi
Abstract
One of the key challenges in empirical studies relates to the identification of the dynamics of bubbles that periodically run up and collapse. This study is an attempt in this field, which initially examines some limitations of one of the relatively new methods in the economic literature as to the identification ...
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One of the key challenges in empirical studies relates to the identification of the dynamics of bubbles that periodically run up and collapse. This study is an attempt in this field, which initially examines some limitations of one of the relatively new methods in the economic literature as to the identification of rational bubbles in the Tehran Stock Exchange for the period of 2009-2020. Then, by assuming the Markov switching regime approach in this area, we have extended the conventional method by taking into account the dynamic interaction of asset prices in the market with the latent factor in the process of bubbles expansion and collapse. It is shown how this framework, while improving the efficiency of detecting financial bubbles through mitigating the specification error of dynamic models compared to existing alternative methods, is capable of incorporating the feature of traders' interactions in the market with no specific assumptions on how they interact, especially with regard to the coordination of their expectations and pursuant trading behavior. The findings resulting from this method indicate the existence of a bubble in asset prices only for the period 2018-2020, as opposed to the use of the conventional method, which implies either no bubble or the existence of two bubbly periods 2012-2014 and 2018-2020. in the Tehran Stock Exchange.
Siab Mamipour; Soghra Jafari; Ziba Sasanian Asl
Abstract
The main purpose of this paper is to investigate the effects of monetary and fiscal policies on the business cycles in the Iranian economy during the period 2004-2016. Markov Switching model has been used with time varying transitional probabilities for the recognition of the business cycle and identifying ...
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The main purpose of this paper is to investigate the effects of monetary and fiscal policies on the business cycles in the Iranian economy during the period 2004-2016. Markov Switching model has been used with time varying transitional probabilities for the recognition of the business cycle and identifying the influencing factors on the probability of staying in a period of recession and boom or the transition from one situation to another. The results of the MSIH(2)-AR(2)[1] model show that both expansionary monetary and fiscal policies increase expansion period, but expansionary monetary policy is more effective in expansionary fiscal policy. During the recession regime, fiscal policy has a greater impact than a monetary policy in the transition from the recession regime. Also, findings show that business cycles in Iranian economy have comovements with changes of oil revenues, but the effect of changes in oil revenues has a different effect on the staying or transition of business cycles. Thus, the increase of oil revenues reduces the probability of staying economic boom regime, but it will increase the transition probability of recession to boom regime. In fact, these results indicate that oil revenues are not managed well during the boom period but there is the relatively good management in the recession regime. [1]- Markov Switching Intercept and Heteroskedasticity terms (2 regimes)-AutoRegressive (2 Lags)
