Iranian Journal of Economic Studies
Volume:9 Issue: 1, Winter and Spring 2020

Improving energy efficiency is one of the most important energy policies in many countries. This study mainly focused on the economic and environmental effects of energy efficiency improvements in Iran’s electricity sector on Iran’s economy using a computable general equilibrium framework. Furthermore, the potential benefits of carbon reduction were explored. The results showed that the most significant change occurred in the sectoral output. Other macroeconomic variables, such as GDP and export, also showed higher levels. Accordingly, it can be asserted that a combination of energy policies, such as carbon pricing and revenue recycling, that are aimed at improving energy efficiency can potentially have positive effects on both the economy and the environment. Therefore, energy efficiency improvements can be considered a cost-effective alternative to promoting sustainable development.

Since the nationalization of the oil industry, especially after the 1979 revolution, Iran has always encountered economic sanctions. The oil embargo and international financial sanctions are the most severe sanctions imposed on Iran and have had significant effects on Iran’s macroeconomic variables. The current study aimed to analyze the effects of economic sanctions on Iran’s macroeconomic variables using a dynamic stochastic general equilibrium (DSGE) model based on the new Keynesian approach. The simulation results showed that the intensification of the oil and international financial sanctions would 1) reduce foreign and government investment, technology innovation, export in the oil sector, and consequently oil production, 2) lead to a higher exchange rate and a decrease in the ratio of the central bank foreign exchange reserves to the monetary base, 3) reduce the GDP and non-oil exports and increase the inflation, which may cause stagflation, 4) increase household consumption and decrease household investment, 5) increase budget deficit, forcing the government to adopt policies to raise current expenditures and maintain housing and urban development budget, which, in turn, will lead to a budget deficit and bond sales. The analysis of various optimal monetary policies in the context of economic sanctions and considering the contingent business interruption (CBI) loss function showed that the optimal simple rule, in the form of the producer price index, targeting monetary policy, could reduce the loss function and increase the importance value of output coefficient in themonetary policy.

The main aim of the present paper is to measure the potential value-added tax (VAT) capacity in Iran using the multiregional input-output model (MIOM) to answer the following question: “how much indirect value-added tax is potentially generated in one region in order to satisfy the production of other regions?” Applying Leontief’s final demand-to-output is not suitable and therefore, Pasinetti’s parsimonious production-to-production approach is utilized. For this purpose, we have used a MIOM covering 9 regions for the year 2016. Based on the existing conventional regional theory, we expect that larger regions have a tendency to contribute more value-added to other regions. Surprisingly, the overall results confirm the prevailing theory as follows: for example, region 6 (the largest region) generates 5.3% of the total value added of region 1, whereas region 7 (the smallest region) is responsible for 1.7% of the total value added of region 1. Similar results have been found on the impact of regions 6 and 7 on the added value of other regions. In addition, based on the logic of VAT system, it is expected that a larger region has a higher impact on VAT capacity in other regions. The overall findings relatively confirm the theoretical prediction as follows: the impact of region 6 on VAT capacity of other regions is 4-12 times more than the impact of the smallest region on the potential VAT capacity of other regions.

Monopoly and negative externalities are two aspects of market failure that affect the market performance. This study extends the Leibenstein approach, a framework to measure the market performance, which evaluates the social welfare costs of market power and environmental inefficiency. To assess the deadweight loss, we capture pollution impacts, on the market performance in an imperfect competition. In doing so, we assess marginal costs and price elasticity of demand by a Translog function, market power by Herfindahl-Hirschman and Lerner indices, and environmental inefficiency by directional distance functions, at a Cournot competition for Iran’s energy-intensive industries at the four-digit ISIC level. Our results demonstrate that the social welfare costs of welfare triangle and economic rent are negligible and include a small amount of welfare costs. Non-ferrous foundry imposes the lowest social cost (1.03% of its production value), and cement, lime and gypsum industries impose the highest social cost (50.7% of their production value). Those industries with more market power pay less attention to the environment. In polluting industries, welfare loss, due to market power, is relatively negligible. However, relatively high cost of social welfare, due to environmental inefficiency, indicates the necessity of levying a green tax to reduce the adverse effects.

Government expense is an important financial tool for empowering the poor. In such a way that the government provides a suitable environment for the business of people by investing in the fields of defense, judiciary, legislation, order and security. In addition, by providing social services such as education, health, social security, and transportation, communication, energy and infrastructure, the government causes an increase in human capacity for earning more money leading to the reduction of poverty and inequality. The purpose of this study is to estimate the optimal amount of government expenses in economic, social and cultural, defense and security, public affairs. Related chapters aim at minimizing income inequality. In this regard, the threshold regression model and the simplex linear programming algorithm are used for estimating the time series data during the period 1971-2019. The results reveal that the optimal amount of government expenditure total should be equal to 19.2% of GDP to reduce the income inequality. Also, for reducing the income inequality, the optimal amount of public, defense, social and economic expenses in GDP should reach 1.1, 2.35, 10.2 and 5.5 percent, respectively. Moreover, among the chapters, the optimal amount of education, health and defense chapters with the highest priority should be 6.5, 2.25, 1.79% of GDP, respectively. Furthermore, other chapters have different effects on income inequality.

After the financial crisis of 2007-2009, in which liquidity problems led to insolvency and consequently the bankruptcy of many large banks and financial institutions such as Lehman Brothers, Basel Committee on Banking Supervision introduced liquidity requirements for the most part to reduce the possibility of bank insolvency caused by liquidity shocks. This research develops an agent-based model of a banking system to be used to analyze the impact of the liquidity requirements on the solvency position of banks. The model devises a banking system with 12 heterogeneous banks in which banks perform their traditional activities namely taking deposits and making loans. Banks can fulfill their liquidity needs by engaging in interbank lending, selling their securities, and using central bank lending assistance. The model aims to study the behavior of different banks in response to imposing liquidity requirements. This model is calibrated using the data of Iranian listed banks during 2018-2020. Liquidity requirements are measured using liquidity coverage ratio, and the solvency position of a bank is measured using the capital adequacy ratio. The results of the simulations demonstrate that as liquidity requirements increase, the solvency position of some banks improves, some banks deteriorate, and some remain unchanged. Regarding this reaction among other various factors, profitability, inflow, and outflow of liquidity, and finally, the outflow rate parameter play an essential role.

Propensity score matching is extensively utilized in estimating the effects of policy interventions and programs for data observations. This method compares two treatment and control groups to make statistical inferences about the significance of the effects of these policies on target variables. Therefore, when using propensity score matching, it is significant to obtain the standard error to estimate the treatment effect. The precise estimations of variance and standard deviation facilitate more efficient statistical testing and more accurate confidence intervals. However, there is no agreement in the literature on the estimation method of standard error; some methods rely on resampling, while others do not. This study compares these methods using Monte Carlo simulation and calculating the Mean Squared Errors (MSE) of these estimators. Our results indicate that Jackknife and standard methods are superior to Abadie and Imbens (2006) bootstrap, and subsampling ones in terms of accuracy. Finally, reviewing Tayyebi et al. (2019) indicated that different methods of estimating variance in the matching estimator led to different statistical inferences in terms of statistical significance.

Wagner's Law states that the relative size of public sector increases with the growth of per capita income. This study examines whether there is empirical evidence that Wagner’s law holds in the Iranian economy using time series annual data over the period 1985-2018 in Iran, applying cointegration and vector error correction modelling (VECM) techniques. In particular, this study provides a special focus on examining the validity of the versions of Wagner’s hypothesis, which supports the existence of long-run relationship between public expenditure and economic growth. The results of the estimates demonstrate that this law holds in Iran. The elasticity of the government expenditures with respect to national income must be greater than one for the Wagner’s law to hold. However, government’s spending on health and education has been less than expected. Therefore, considering all the government’s spending, Wagner's law is valid in Iran. On the other hand, by examining government expenditures in health and education sector as the most important part of the government expenditures, it is seen that the revenue elasticity of government expenditures in the health and education sectors is less than one. Accordingly, our estimates for Iran do not confirm this law. Although the absolute size of the public sector grows when the income increases, its rate of growth in these sectors is substantially lower than the growth of income. This could suggest that the government does not pay enough attention to health and education sectors and that these are not priorities of the government.

The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and high fluctuations in Iran during the spring 2013 and winter 2018. For this purpose, time-series data of the daily average electricity price was decomposed into one approximation series (low frequency) and four details series (high frequency) utilizing the wavelet transform technique. The approximation and details series are estimated and predicted by ARIMA and GARCH models, respectively. Then, the electricity price is predicted by reconstructing and composing the forecasted values of different frequencies as a proposed method (Wavelet-ARMA-GARCH). The results demonstrated that the proposed method has higher predictive power and can forecast volatility of electricity prices more accurately by taking into consideration different domains of the time-frequency; although, more errors are produced if the wavelet transform process is not used. The mean absolute percentage error values of the proposed method during spring 2017 to winter 2018 are significantly less than that of the alternative method, and the proposed method can better and more accurately capture the complex features of electricity prices.

The exchange rate and international oil price are key variables to cause the effects of external shock on economics and the relationship to domestic economy. Since in countries like Iran, most government revenues come from exchange earnings from the international markets by oil exports, the impact of these two variables on the economy has significant consequences. In addition, it should be considered how fluctuations in the exchange rate and international oil prices can impact policy and international relations. According to the international trade perspective, it is believed that the exchange rate affects the economy through the changes in exports and imports commodities; therefore, expectations of the exchange rate will affect the price of the products traded. Moreover, the impact of oil price on the production of commodities changes the level of supply for activities and income of institutions through changes in the production factors and intermediary imports price. We conclude that if any change in both exchange rate and oil prices occurs, it will cause a change in welfare indicators. This research has therefore arisen to fill this void in the literature. Moreover, it utilizes a logistic model to represent the change in the exchange rate and oil price. Based on empirical results, a recursive computable general equilibrium model is constructed to predict future social welfare and simulate the impact of exchange rate fluctuations along with the oil price shock. The results are presented in different scenarios using the 2011 Social Accounting Matrix (SAM).