Journal of Economic Modeling Research

Studying how monetary and fiscal policy affects specific macroeconomic variables, especially in the industrial sector, using an IO-DSGE model.

fakhreddin fakhrhosseini

This study explores how monetary and fiscal policies influence certain macroeconomic variables through a multi-sector stochastic dynamic general equilibrium (DSGE) model that includes input-output (IO) analysis. The focus is on the industrial sector, taking into account the specific conditions for Iran. The research uses quarterly data from Spring 2006 to Spring 2023 and references the 2016 input-output table provided by the Central Bank. In the nonlinear model, the original 89 activities from the input-output table have been simplified to 9, which includes the industrial sector and eight other sectors. Model parameters are estimated based on previous studies of the Iranian economy and data from the input-output table. The model's effectiveness is assessed by comparing simulation results with real-world data, which shows a strong correlation. The simulations indicate that increases in the money supply result in only a small rise in both total and industrial output. This leads to a slight decrease in total employment, while employment in the industrial sector experiences a minor increase. Similarly, increases in government spending show tiny improvements in overall and industrial output, accompanied by a slight drop in total employment and a small rise in the industrial sector. The findings suggest that the effects of monetary and fiscal policy shocks on output and employment, when accounting for input-output relationships and dividing the economy into nine sectors, better reflect the realities of the Iranian economy. Given the minimal influence of these policies on boosting production and economic growth, it is essential for them to be targeted and supported by additional measures and strategies.

Investigating the effects of globalization and energy consumption on carbon dioxide emissions in Iran: the application of particle swarm optimization algorithm in fuzzy regression model with symmetric and asymmetric coefficients

Reza ashrafganjoei

Although many factors in economic growth and development are scientific, but the global impact and energy consumption have a prominent role in the economy according to the evidence. In the meantime, we should not ignore the consequences of environmental destruction. In the present study, the effect of uncertainty of globalization and energy consumption on CO2 gas emission has been investigated with the help of fuzzy regression model with symmetric and asymmetric coefficient for the time period of 1369-1400. According to the average scale of the phased vessel model, the three boundaries and the bottom are calculated for each of the investigated changes under different uncertainty conditions using the particle swarm algorithm. Examining the effect of the limits related to the uncertainty of globalization and energy consumption on the amount of CO2 gas emissions indicates that as the degree of membership approaches 0.1 to the degree of membership 0.9, first, the amount of CO2 gas emissions up to be Membership increased by 0.4 and then decreased in a downward trend of CO2 emissions. This impressive trend is also true for the middle and lower limits. From this, it can be stated that the effect of the uncertainty of energy consumption on the amount of CO2 emissions is similar to an inverted U. It is noteworthy that the trend of energy consumption compared to globalization increases the amount of CO2 emissions, so it can be said that the amount of CO2 emissions is not the result of the refugee hypothesis.

Analysis of the Impact of Factors Affecting Ecological Footprint with Emphasis on Energy Consumption Intensity in Iran: TVP-VAR Approach

Mohammad hosein Karim

The main purpose of this study is to investigate the effect of factors affecting the ecological footprint with an emphasis on the role of energy consumption intensity in Iran using the Vector Autoregression Model with Variable Parameters Over Time (TVP-VAR). The ecological footprint reflects the environmental constraints of communities and the extent to which the environment is destroyed by exceeding these limitations. Due to the increasing intensity of energy consumption, Iran is faced with a significant ecological footprint in its economic activities, which requires the root causes of the factors affecting it. Other research variables include the degree of urbanization, human development, financial development, trade openness, and GDP per capita in the period from 1990 to 2021. The results show that increasing the intensity of energy consumption causes a positive and significant increase over time on the ecological footprint. The effect of other research variables on the ecological footprint was also in accordance with theoretical expectations. These findings emphasize that the type and source of energy consumed, as well as the production processes, play an important role in this relationship. Also, the analyses show that environmental sustainability decreases with increasing energy consumption and the ecological footprint of

Comparison of I-O and CGE models by Simulating the Impact of Price Liberalization of Electricity, Distribution of Natural Gas and Water on the Output and Prices of the Main Sectors of Iran Economy

farid fAYAZMANESH

Although, input-output (I-O) and general equilibrium (CGE) models are systems based on interrelations between sectors and economic agents. However, they are very different in terms of design complexity, model solving techniques, required input data, outcomes, theorical structure and adopted assumptions.
Therefore, the results of simulating the effects of an economic policy using each of these models will definitely be different. But, avoiding complexity, difficult solving techniques, collecting large amount of data and so on, sometimes make us to use simpler, although less accurate, models. In this case, obviously, the assumptions and restrictions of the model are to be fully noticed, when interpreting the outcomes of simulation. Otherwise, incorrect decision making will be inevitable.In this paper, we assess the impact of price liberalization of electricity, distribution of natural Gas and water on the output and prices of the main sectors of Iran economy. This is done by using a I-O and a CGE, both designed by autors. The simulation is implemented by cutting subsidy payed to final and intermediate consumption of electricity, distribution of natural Gas and water. The outcomes are largely different regarding the amount and the direction of sectoral output and price changes. While the outcomes of I-O model are against this policy, the results of CGE model, in which total output and household consumption increase, are in favor of it. The rise of demand in tradeable agriculture and industries and mining are accompanied with more import, so that their new equilibrium output will be lesser. But, output of non-tradeable construction and low tradeable services increase. The increase of crude oil and natural gas are totaly exported.

The relationship between credit risk, cost gap ratio and banks' efficiency in selecte Islamic and conventional countries

mostafa Rajabi

In Islamic and conventional banks, there may always be differences in efficiency, cost gap ratio and credit risk; Therefore, the purpose of this study was to investigate the relationship between credit risk, cost gap ratio and efficiency of banks in selected Islamic and conventional countries. For this purpose, credit risk, efficiency and cost gap ratio were calculated for 50 Islamic banks and 50 non-Islamic (conventional) banks during the years 2013-2019 and regard, the results of the t-test showed that the credit risk, inefficiency and cost gap ratio are higher in Islamic banks than conventional banks. Also, the results of the Granger causality test showed that there is a bidirectional causality relationship between inefficiency and credit risk. But this relationship is a little weak. There is no causal relationship between credit risk and cost gap ratio, and there is a strong two-way causality relationship between inefficiency and cost gap ratio. The results in Islamic banks are almost similar to all banks. However, in Islamic banks, credit risk is not the Grangerian cause of inefficiency. Also, the significance level of other causal relationships is much higher. For conventional banks, there is no causal relationship between inefficiency and credit risk. There is no causal relationship between credit risk and cost gap ratio, and there is a two-way causality relationship between inefficiency and cost gap ratio. In addition, the results of variance analysis indicate that the cost gap and inefficiency have a close relationship with each other and their effectiveness is high. Credit risk also has a more or less effect on inefficiency during future periods. In Islamic banks, the effects of inefficiency and cost gap on credit risk are slightly higher. But the inefficiency of the cost gap has a high effectiveness. In conventional banks, credit risk has the same effectiveness as Islamic banks, but its effectiveness is somewhat less. Also, inefficiency has less effects than the cost gap. The cost gap, like Islamic banks, has a high effectiveness of inefficiency, and this effectiveness decreases over time.

The Role of Productive Capacity in Renewable Electricity Generation: A Dynamic Panel Threshold Model

Mahboubeh Jafari

Promoting electricity generation from renewable energy sources has emerged as a cornerstone of sustainable development strategies worldwide to mitigate greenhouse gas emissions and address the pressing challenges of climate change. This study aims to investigate the nonlinear relationship between the Productive Capacity Index (PCI) and renewable electricity generation across a sample of selected developing countries during the period 2000–2022. To this end, the dynamic panel threshold model proposed by Kremer et al. (2013) is utilized, as it enables the analysis of nonlinear interactions among variables in panel data while addressing potential endogeneity. Our findings reveal a non-linear relationship between PCI and renewable electricity generation. Importantly, the influence of PCI on the share of electricity generated from renewable sources intensifies beyond a specific threshold value. This implies that as PCI levels increase, their impact on clean energy production becomes more significant, emphasizing the importance of advancing productive capacities to accelerate the transition to renewable energy. Furthermore, the results underscore the critical role of several key factors in enhancing renewable electricity generation. Rising geopolitical risks, improved financial development, greater trade openness, and an increased share of gross fixed capital formation in GDP are identified as pivotal drivers that positively contribute to the expansion of renewable electricity generation. Conversely, weak environmental policies can significantly hinder this progress. Furthermore, the Dumitrescu and Hurlin (2012) panel causality test confirms the existence of a bidirectional causal relationship between the share of renewable electricity generation and the other explanatory variables. This study highlights the critical need to build and strengthen productive capacity to support the growth of renewable energy. The findings provide a valuable foundation for informed decision-making by policymakers and planners in developing nations.