فصلنامه پژوهش های اقتصادی ایران
پیاپی 65 (زمستان 1394)

Using a Markov Jumping Linear Quadratic (MJLQ) method, this paper examines the impact of financial uncertainty on monetary policy in Iran in the context of a new Keynesian model. This model allows us to study the impact of financial uncertainty on inflation and output gap. We allow the economy to switch between normal and abnormal states. Our model is estimated in two stages. We first estimate the parameters of our normal model by using maximum likelihood method. In the next stage, we use the parameters obtained in the first stage and Apply Metropolis-Hastings random walk method to estimate the parameters of our MJLQ model. This allows to investigate the reaction of key variables to shocks in inflation, output gap and interest spread. We find out that the reaction of monetary policy to these three shocks under certainty case in the abnormal time model is stronger than those under uncertainty case. This finding might have important policy implication for authorities when conducting monetary policy in the presence of financial frictions.

In developing countries like Iran, fiscal policy instruments- especially taxes- affect the competitive power of financial markets and the performance of banking and non- banking institutions in these markets. Thus, the quality of combination of financial markets and tax policies for economic growth has raised many issues. On the one hand, theories state that any increase in taxes leads to a reduction in investment funds and has an opposite impact on financial markets. On the other hand, they state that taxes reduce market fluctuations and prevent financial crises. This paper studies the impact of taxes on financial market in Iran during 1970 – 2011 by using Bounds test and Auto-Regressive Distributed Lag (ARDL) model. Results show that taxation has a positive effect on financial markets. This indicates that the role of taxation, according to improvements in state’s tax system in recent years, has become more prominent in the further development of financial markets.

Iran is flaring about 30 million cubic meters of associated gas per day in onshore oil fields. Suboptimality of economic extraction and production of exhaustible natural resources pawn the national benefits. Therefore, the main purpose of this paper is analyising the economic and technical feasibility aspects of reusing flared associated gas based on Capital Asset Pricing Model (CAPM). In this study time series data of average associated flared gas from 44 Iranian onshore oil fields has been employed. Additionally, three investment scenarios mean gas injection to the oil fields, electricity production and final consumption have been considered. Results of this study show that such oil fields produce less than 3 million cubic meters associated gas per day, gas injection to oil fields is the optimum alternative whereas using of associated gas to electricity generation is advised for other scenario.

The association between money and prices has long been debated in various economic schools. Although there are different views, most economists agree that in the long run, inflation is a monetary phenomenon and its main cause is liquidity growth. Several models have been designed in order to clarify the monetary aspect of inflation, how to forecast it and the awareness of how it moves in the economy. One of the models that have been considered recently is the P-Star model which draws on the quantity theory of money. The framework of P-Star model is based on the fact that inflation in long run is a monetary phenomenon and the price level moves proportional to the money supply in the economy. In this research by using seasonal data of Iran, two different alternatives of P-Star model have been tested by considering liquidity gap, velocity gap and output gap. In order to estimate the liquidity gap, ARDL Approach has been used to estimate the demand for liquidity. For velocity of money gap, Hodrick-Prescott filter was Applied and by using state-space models and the Kalman filter, output gap was estimated. The results indicate that the P-Star model with liquidity gap and velocity and output gap have satisfactory explanatory power of inflation. According to the outcomes of static and dynamic forecasts, the P-Star model with liquidity gap has higher predictive power of inflation.

In this paper, following Maćkowiak, Moench and Wiederholt (2009), the reaction of sectoral price indexes to aggregate and idiosyncratic shocks has been evaluated using Bayesian Dynamic Factor Model. The separation of the reaction of prices to these two types of shocks has been done in order to identify the pricing model that is more compatible with Iranian economy. In case of existence of any significant difference in speeds and sizes of price reaction with respect to these shocks, we can conclude that some of the conventional price setting models such as Calvo could not be able to explain the differences. Therefore, for the purpose of explaining the price setting behavior in Iran, alternative pricing models should be evaluated. The results of this study clearly show that there is a significant difference between the reaction of price indexes to aggregate and sectoral shocks. Based on the results, rational inattention model of Mackowiak and Wiederholt (2009a) is more consistent with the stylized facts of Iran’s economy in comparison with the conventional pricing models.

Exchange rate pass-through is one of the most important issues in the international economic studies. Determining the degree of exchange rate pass-through can be used to define the effectiveness of foreign policy, market structure and exporters behavior. The main objective of this study is to investigate the exchange rate pass-through to export prices of Iranian pistachios during the period 1961-2011. In the previous studies, the exchange rate pass-through was assumed to be fixed during different years. This assumption is not consistent with reality, because many factors can influence the exchange rate pass-through. In this study, sensitivity analysis in the framework of artificial neural network is used to address this shortcoming. The results shows that exchange rate pass-through to Iran's pistachio export prices has been more than 70 percent, and its trend has been periodic. Furthermore, the results showed that there is a direct relationship between exchange rate fluctuations and Iranian pistachio export prices. Thus, by reducing exchange rate volatility, it is possible to supply pistachio with lower prices to the world markets. Considering the high elasticity of demand for the Iranian pistachio prices, a reduction in prices would increase revenues of exporters. Incidentally, given the high elasticity of export demand for Iran's pistachio, the revenues from the export of this product can be increased by reducing the cost of pistachio production.