atefe alahverdi; Saeed Daei-Karimzadeh; sara ghobadi
Abstract
In recent years, the financial condition index (FCI) has been used in many countries as an important index to determine the state of macroeconomic policies. For this purpose, in the present study, the effects of financial condition index on macroeconomic variables were investigated by applying the time-varying ...
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In recent years, the financial condition index (FCI) has been used in many countries as an important index to determine the state of macroeconomic policies. For this purpose, in the present study, the effects of financial condition index on macroeconomic variables were investigated by applying the time-varying parameter factor-augmented vector autoregressive model (TVP-FAVAR) and using quarterly data during the period (1991-2019). The results indicate that the response type and response rate of macroeconomic variables were different due to the financial condition index shock over time, and this indicates the necessity of employing the parameter - variable approach. According to the obtained results , The unemployment rate and economic growth rate variables in the short and long term showed a Negative and positive response to behavioral changes in the financial condition index variable, respectively; The effects of the financial Conditions Index shock on the inflation rate variable appear after one period; However, the response of this variable to the financial condition index shock in the short and long term has been different according to the conditions prevailing on the economy of the country . Also, the financial conditions index shock in the short run has improved the Gini coefficient variable, but in the long run, especially in the late 2010s has rised the income gap. The response of the budget deficit variable to the financial condition index shock in the whole period under review was positive and the financial condition index shock has increased the government budget deficit.
Azita Sheikhbahaie; saeed Daei-Karimzadeh; sara ghobadi
Abstract
The Clean Development Mechanism (CDM) is an international cooperation mechanism that provides developing countries to achieve economic growth by promoting investment in clean energy projects. This study investigates the effect of investments on renewable energy through clean development mechanism in ...
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The Clean Development Mechanism (CDM) is an international cooperation mechanism that provides developing countries to achieve economic growth by promoting investment in clean energy projects. This study investigates the effect of investments on renewable energy through clean development mechanism in a selection of developing countries using the method of differences in differences during the period 2001-2018. The purpose of this study is to compare the spread of renewable energy in countries that accepted the Clean Development Mechanism in comparison with others. The effect of implementing this mechanism in developing countries with poor financial markets compared to developing countries with advanced financial markets is also examined. The results show that the implementation of clean development mechanism in developing countries leads to the expansion of renewable energy. This mechanism can finance clean energy projects and transfer modern technologies to these countries. Also, according to the results, the effect of implementing the clean development mechanism in developing countries with poor financial markets is far more developed than advanced financial markets.
Economic Growth
ramiar refaei; morteza sameti; sara ghobadi
Abstract
The history of Iran's economy after the revolution has been in recession for some years and, with the 70s, this trend has deepened, and with the 1990s it seems that the real GDP trend is making serious changes. In this paper, the Markov chain Monte Carlo and Byesian approach are used to simulate the ...
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The history of Iran's economy after the revolution has been in recession for some years and, with the 70s, this trend has deepened, and with the 1990s it seems that the real GDP trend is making serious changes. In this paper, the Markov chain Monte Carlo and Byesian approach are used to simulate the effects of factors affecting the economic recession in Iran during the years 1979- 2016. The results show that the Bayesian approach confirm the results of the model estimation using the Monte Carlo Markov chain approach, and at a reliable level, 97.5% of the coefficients of the variables are statistically significant and reliable. so, the most influential variables were estimated on the economic recession in Iran, are exchange rate changes, crude oil prices, and real GDP. The results also show that the matrix of Bayes factors for all pairings of models is reliable. The later probabilities of regimes and the likelihood ratio indicate that the change points in the sixth model are different with the rest of the models, so the regime change is happening in the sixth model.
