مجله سیاست گذاری اقتصادی
سال سیزدهم شماره 26 (پاییز و زمستان 1400)

Due to the widespread use of discrete choice experiments in extracting preferences, the present study uses this method in order to identify and evaluate the variables affecting the decisions and preferences of depositors in banks with an ethical approach. At first, by studying foreign and domestic research works, the components related to ethical banking were identified. Then, in consultation with banking experts, eight variables including »Deposit interest rates«, »Bank ownership status«, »Profit and profitability objectives«, »Environmental objectives«, »Loan interest-free objectives«, "Poverty reduction and unemployment reduction objectives«, »Cultural and artistic objectives«, and »Accountability And the bank's responsibility for goals and priorities« were selected as important factors influencing the decisions of depositors in ethical banks (assuming the stability of other economic conditions).

Given the widespread use of the discrete choice experiment model in extracting preferences for goods and services for which there is either no market or the market is incomplete, this research seeks to extract and evaluate the willingness to pay for non-market variables of ethical banking. It is then followed by several other steps. First, using D-Optimal, the final options were selected from all the possible options to examine the preferences of ethical banking depositors; the selection of the number of alternatives and the set of questions was based on what was found common in such studies. The set of prepared selections and the requested economic information were distributed in the form of 100 questionnaires randomly among the target population. About 82 completed questionnaires were collected. It should be noted that the sample sizes, despite the lack of a clear criterion for determining it and the lack of financial support for the implementation of the research, was almost consistent with the average sample size in similar foreign works.

Regarding the depositors' preferences for ethical banking, the results show that, out of the total eight variables included in the model, four variables including »Deposit interest rate«, »Bank ownership status«, »Poverty reduction targets and unemployment reduction« and »Bank responsibility for goals and priorities« have significant effects on the decisions of depositors of banks with an ethical approach. In other words, according to the coding performed, the increased interest rate on deposits, the governmental nature of the type of bank, the pursuit of goals to reduce poverty and unemployment by the bank and the bank's accountability for goals and priorities make it likely for depositors to turn to ethical banks. While the other four variables, despite their importance in theoretical discussions of ethical banking, are statistically meaningless, which confirms that such activities are not attractive to depositors and, therefore, they are not inclined to pursue such activities. Including them in the portfolio offered by the bank or credit institution has, thus, no effect on the willingness and likelihood of referring to banks with an ethical approach. In the respect of willingness to pay, considering the interest rate of the deposit as a normalizing monetary variable, the variable »Objectives to reduce poverty and reduce unemployment« has the most positive impact on depositors' decisions among other model variables. So, every person is willing to give up the 5.13% interest rate on deposits, but the funds deposited with the bank will be used in order to reduce the level of poverty and unemployment or in exchange for ignoring this amount of interest on the deposit of financial assets to be spent in this particular way. In contrast, the variable of bank ownership (whether private or public) had the least effect on the decision-making portfolio of the respondents (depositors). This is because each person is only willing to give up about 1% of the deposit interest if the bank is state-owned. It indicates the low importance of the variable of the type of bank ownership in the portfolio of the preferences of the depositors of ethical banks.

From the respondents' point of view, the concept of ethical banking is summarized only in the context of the goals of reducing poverty and unemployment, and it has the highest priority in the basket of people’s preferences. However, the ethics of banking paradigm has various dimensions, and it seems that depositors are not convinced in relation to the other dimensions and related components, including environmental issues and accountability and supervision.

The goal of a food and nutrition (FN) system is to provide continuously everybody with adequate healthy food consistent with their preferences. Failure to achieve this goal is a major obstacle to attain individual and social development goals. Then, it is a matter of importance to examine the FN status of households and identify the factors affecting their FN status. This research is conducted to identify the individual factors (especially size of the household, household head education and his marital status) affecting the nutrition security of households in urban areas of Iran. Food security is defined as the availability and the access of food to all people, whereas nutrition security demands the intake of a wide range of foods which provides the essential needed nutrients.

We analyzed the data from a sample of 18809 households living in all the provinces in Iran in 2016. The data were collected by the Statistical Center of Iran through Household Expenditure and Income project. A nutrition insecurity index was defined based on the “suitable and preferable food basket for Iranian households”. There are 14 food groups required to meet essential micronutrient needs for human body. For each group a minimum standard level is determined. The household is moderately insecure if it is undernourished in more than seven food groups and severely insecure if it is undernourished in more than 10 food groups. The insecure status of a household is denoted by 1 and its secure status is marked by 0. As the regressor takes two values (0 or 1), the Logit model is employed to run the empirical model.Regressors are a variety of socio-economic variables. Through trial and error, we found seven factors determining the nutrition security of the households including annual per capita income of the household, house ownership status, age of household head, contribution ratio (ratio of the number of employed members to household size), marital status of the household head, the household head’s education, and household size (the number of members). Multicollinearity was also examined. In a logit model, F-statistic test is not suitable to identify multicollinearity. Therefore, we used partial correlation coefficients and VIF tests. 

The results showed that 82 percent of the households in more than seven groups (moderate nutrition insecurity) and 45 percent of the households in more than 10 groups (severe nutrition insecurity) out of 14 food groups were undernourished.In case of moderate nutrition insecurity, all of the explanatory variables were significant at the level of 1 percent p-value, but, for household head education, it was significant at 10 percent. Also, all the variables explained the severe nutrition insecurity at the level of 1 percent.The marginal effects of the determining factors were also calculated. The annual per capita income, the contribution rate and the size of the household were known as the most effective determinants of nutrition security of the household. The marital status of the household head and house ownership came next. Household age and education were slightly effective as well. The households with married heads were more nutrition secure although their annual per capita expenditure on food was less than those with single heads. Marriage seems to have a positive effect on the household food standards and quality.Few researches have met the fact that education has negative effect on nutrition security. This research is one of them. The households in which the heads are of higher education level, in our sample, had higher annual per capita incomes, higher annual per capita food expenditures, bigger sizes and smaller contribution ratios. It seems that although higher education level increases the quantity of food consumption, it fails to make the quality of it better..All the partial correlation coefficients of the explanatory variables were significant at 5 percent (except for contribution ratio and house ownership, which was insignificant). But the biggest coefficient was 45 percent, so small that we could say there was no sign of multicollinearity. Of course, it does not confirm the lack of multicollinearity. VIF also did not show any clue of multicollinearity. All the variable VIFs were between 1 and 2, much smaller than 10, which is alarming.

In search of the factors affecting the nutrition security of urban households in Iran, we raised questions about three variables including household size, household head’s marital status and his education level. Our data from 18809 households in all the provinces suggested the following:As the household size grows bigger, the family becomes more nutrition insecure.As the household head’s education level is higher, the family becomes more nutrition insecure.Households with married heads are more nutrition secure. It seems that the nutrition standard and quality is better in these families although they spend less per capita food than households with single heads.The other factors identified were the annual per capita income of household, house ownership status, age of household head, and contribution ratio.

Exchange rate volatility can affect the performance of macroeconomics, especially the competitiveness of countries. Real exchange rate volatility indicates the instability and uncertainty in relative prices. It creates an unstable and uncertain environment in the economy. Therefore, the study of the impacts of exchange rate volatility has a great importance. In order to study its effect, it is necessary to first measure the volatility as a quantitative variable. For this purpose, various econometric methods have been introduced, such as the Generalized Autoregressive Conditional Heterogeneity (GARCH). In general, choosing an accurate method for modeling and predicting volatility in economic variables has always been one of the goals of many studies. If volatility is not calculated accurately, misleading experimental results are obtained. After the critique of Lucas (1976), it became important to pay attention to models with time variable coefficients. One of the implications of Lucas' critique is that the estimated coefficients to express the relationship between the variables cannot be stable. This issue is especially important in developing countries where the process of changing economic structures is faster and wider. So, the purpose of this study is to introduce a time-varying GARCH model to calculate the exchange rate volatility in Iran.

The research was based on the monthly exchange rate data (US dollar to Rial) in the market during 1985-2019. The data were extracted from the online database of the Central Bank of Iran. For the calculation of the volatility in economic variables, the tendency to use GARCH models is greater than other models. Among the GARCH models, GARCH (1,1) is the most popular. However, according to Stock and Watson (2008), because of structural breaks, the most important problems of GARCH models is that they cannot make accurate predictions over the time. This gave more attention to time-varying parameter models and Markov chain Monte Carlo models. In these models, estimation coefficients can change over time. Also, the study of the financial time series shows that most of them are influenced by domestic or foreign political, economic and social events, such as financial crisis, oil shocks, war, political instability and sudden changes in foreign exchange policies. The effects of these events sometimes remain in the market for a long time. Therefore, it can be said that models with fixed coefficients do not have the ability to formulate the behavior of exchange rates, especially in the long-term horizons. Thus, it is necessary to use time-varying models with variable coefficients over time. In this study, in addition to conventional GARCH models, a time varying GARCH (TVGARCH) is introduced to show the different behaviors of exchange rate over time. For this purpose, the TVP-SVM model based on the model introduced by Koopman and Hol Uspensky (2002) is used to examine the exchange rate volatility in Iran. In this study, following Chan (2017), the Monte Carlo Markov Chain (MCMC) approach is used to estimate fixed coefficients and variable coefficients over time. Also, the Bayesian approach and the Markov chain algorithm have been used to simulate the prior distribution if common functions.

In order to calculate exchange rate volatility using GARCH family models, the ARIMA model was first estimated using the Box-Jenkins method, and then the GARCH model was estimated on the ARIMA model residuals.The results of the Zivot- Andrews unit root test showed that the exchange rate has a non-stationary level. The test also confirmed the existence of a structural break in the time series. The estimated values ​​for the coefficients of the GARCH and EGARCH models showed that the conditional volatility in this period is positively affected by the amount of variance in the previous period. Also, more than 95% of the variance of each period is transferred to the next period. The estimated coefficients also showed that there is a significant difference between the effect of good and bad news on exchange rate volatility; good news (i.e., the news that increases the dollar price) compared to bad news (i.e., the news that decreases the dollar price) have greater impacts.As the results of the TVGARCH model showed, the volatility average was 0.358 with 90% confidence, and the logarithm of the variance index was, thus, in the range of -0.79 to 1.557. In the calculations, ϕ represented the effect of the variance of the previous period on the variance of the current period. It was positive and indicated that approximately 96% of the volatility created in each period was transferred to the next period. Also, α represented the relationship between the exchange rate volatility and the exchange rate in each period. The average obtained for this coefficient was positive, implying that, in periods when the exchange rate increases, the exchange rate volatility is higher.According to the comparisons performed on the sample and based on the MSE criterion, TVGARCH is the most accurate, and GARCH is more accurate than EGARCH. Moreover, according to the QLIKE criterion, the TVGARCH model is more powerful than the other two conventional models, and the EGARCH model has a higher accuracy than GARCH.

According to the results, the TV-GARCH model is more powerful than conventional GARCH models. This indicates structural failure and changes in the behavior of the exchange rate in the Iranian economy. It has caused the relationship between the components of the conditional variance to change over time. In other words, there are different values ​​for GARCH coefficients in different periods. According to the results of the TV-GARCH model, the relationship between exchange rate and volatility has been varied over the time, which implies changes in the behavior and motivation of economic agents and the structural changes in the Iranian economy. According to the results, the use of the TV-GARCH model instead of the conventional GARCH with fixed coefficients is recommended.

In recent decades, the increase in the financial sector, compared to the real sector of the economy, and the rising inflation have made individuals and firms invest part of their resources in the financial markets to earn money and maintain their purchasing power. Therefore, the financial sector has expanded significantly compared to the real sector and beset Iran's economy with the financialization phenomenon. Financialization is a process in which the increase in the income of non-financial firms due to their activities in the financial sector and the rise in the participation of individuals in financial activities motivated by profit leads to a significant expansion of the financial sector. The rising returns of the financial sector increase the attractiveness of investment and, hence, the financial sector income. The widening income gap between the financial and real sectors of the economy worsens the income distribution. Moreover, if investment in the financial sector leads to a reduction in investment in productive activities, economic growth in the real sector will decline. Therefore, there is a close relationship between financial sector performance, economic growth, and income inequality in the financialization process. Because the total savings is affected by economic growth and income inequality (Schmidt-Hubble and Seron, 2000), financialization affects the society's savings through economic growth and income inequality. The impact of economic growth is positive on savings; however, the influence of income inequality on savings varies according to the economic structure, income level, and financial market conditions of each country (Bofinger and Scheuermeyer, 2018). Consequently, the final impact of financialization on savings is ambiguous and depends on the net effect of economic growth and income inequality on savings.Therefore, understanding the impact of financialization on national savings allows policymakers to improve the national savings by adopting appropriate strategies to address the deficiencies of financial markets.

To analyze the relationships among the variables, following the work of Schmidt-Hubble and Seron (2000) and Gangor et al. (2014), national savings are considered as a function of the logarithm of financialization, logarithm of GDP, income inequality, real interest rate, and dependency burden logarithm. The ratio of the financial sector value-added to GDP is used to measure financialization following Van Arnum and Naples (2013). To convert the nominal data into real data, the consumer price index is used for the base year of 2004. The source of data is the Statistics Center and the Central Bank of Iran and includes the data of 1988-2020. In this study, the variables of GDP and financialization have a seasonal frequency, and the other variables have an annual frequency. Hence, the MIDAS approach is applied to examine the effect of financialization on national savings. Using the MIDAS approach, it is possible to estimate the coefficients of the variables with different frequencies (Noferesti et al., 2018).

The findings showed that the logarithm of financialization has a negative and significant effect on national savings in Iran. In other words, the expansion of the financial sector has led to a reduction in national savings. Also, the logarithm of GDP has a positive and significant effect on the national savings logarithm. Economic growth is considered a principal factor affecting savings. Increasing economic growth leads to an increase in national savings by raising the income of economic factors. The Gini coefficient leaves a negative and significant impact on the national savings logarithm. A rise in income inequality means an increase and a decline in the income of the rich and the poor, respectively. As income falls, people prefer to reduce their savings and maintain their current level of consumption. Since the number of the poor is more than the rich, in a country, the final effect of reducing the poor individuals' savings is greater than the effect of raising the rich individuals' savings. The real interest rate has a positive and significant impact on the national savings logarithm. With interest rates rising due to the enhanced attraction of investment, most of the income is allocated to saving. Finally, the burden of dependency has a negative and significant effect on the national savings logarithm. Increasing the dependency burden reduces the national savings due to increased consumption expenditures.

In Iran, the economic problems, rising inflation, and the expansion of the recession led investors and firms to increasingly invest their capital in financial markets to keep the power purchase and make a profit. Thus, the financial sector grew and expanded significantly compared to the real sector. The inefficiency of the financial system in the country led to the diversion of resources from productive activities to unproductive inflationary activities, despite the increase in firms and individual participation in financial markets. Therefore, along with the demand reduction of domestic products, financialization caused a decrease in the real sector production of the country. Firms of the real sector were forced to invest part of their capital in the financial section to prevent bankruptcy due to declining production and maintain the value of their capital in the face of inflation. Also firms reduced the production costs by decreasing wages and employment. Thus, a decline in the number of workers and economic growth with rising inflation resulted in a reduction in the real income of individuals and firms. As a result, the progress and expansion of financialization brings about a reduction in economic growth and national savings.

Taxes are one of the main sources of the government revenue. An important source of taxation is payrolls. In recent years, payroll tax revenues have accounted for a large share of tax revenues. Thus, one way in which the government can establish the superiority of tax revenues over oil revenues is through payroll taxes. Increasing the payroll tax rate, as the tax policy discussed in this paper, will have effects on economic variables that need to be studied. Economic growth is an important macroeconomic variable that indicate the economic development index of a country. In Iran, economic growth has always been the focus of governments and economic policy makers. So, in any development program, an indicator of development is economic growth. Therefore, this research seeks to examine the effect of increasing the payroll tax rate on Iran's economic growth.
In this study, the Computable General Equilibrium (CGE) method is used to investigate the economic effects of implementing the payroll tax. In CGE model, the application of each policy in the model occurs by changing the exogenous parameters. In CGE model, the source of data is usually a matrix called the Social Accounting Matrix (SAM). A social accounting matrix is ​​a square matrix in which each account is located at the intersection of a row and a column. This matrix examines the numerical information of the economy comprehensively. Each currency represents the payment from the account on the column to the account on the row. The social accounting matrix shows the relationships between the main actors of each economy, including producers, factors of production, consumers, and institutions. There are also foreign actors in the form of classified accounts, including production account, factors of production account, institutions account, accumulation account (saving), and the account of the other world. The latest SAM of Iran is related to the year 2011, which was prepared by the Parliamentary Research Center. In this paper, it is used as a source of information. Based on above data, the model is calibrated to ensure the validity of the research. Then, the solution of the calibrated model is used as the basis equilibrium with which the results of the experimental test of the model are compared. Finally, the simulation of the policy of increasing the payroll tax rate is done in the research model, which includes several steps including the selection of  the policy parameter in the model (payroll tax rate), determination of the initial value of the policy parameter, calibration of the initial values, change of the policy parameter in the model (applying scenarios of 5%, 10% and 15% increase in the payroll tax rate), reimplementation of the model, determination of the new amount of endogenous variables (including economic growth), and  calculation of the percentage of changes in endogenous variables (analysis of the effects of higher payroll tax rates on economic growth). All the above operations are performed in the programming space of the GAMS software.
In the first step, by estimating the model and using SAM data, the parameters of the production and trade block of the research model, including substitution elasticity, share and transfer parameters in CES and CET functions, were obtained. In the next step, the simulation of research scenarios was done. It showed that increasing the payroll tax rate can reduce the supply of the factor of production and increase wages. Also, the effect of increasing the payroll tax rate on wages and employment is negative, but this effect is not significant. Increasing the payroll tax rate and reducing the level of employment reduce the gross domestic product (GDP) and the economic growth. Of course, like the change in the level of employment, the change in the economic growth is not as significant as the change in the payroll tax rate. Increasing the rate of payroll tax increases the government's tax revenues and, consequently, increases the total government revenue. So, by applying higher rates, the government revenue increases even more. The results of the sensitivity analysis showed that the research model is not very sensitive to different elasticities, and the differences are not significant. Therefore, the model is highly accurate, and one can rely on the results of the impacts of increasing the payroll tax rate on the economic growth and the other variables under the research model.
It is shown that increasing the payroll tax rate leads to increased wages and imperceptible reduction of the employment and economic growth. On the other hand, the positive economic effects of implementing this tax policy are an increase in tax revenues and government revenues. The policy makers' goal of increasing the payroll tax rate is mainly to increase government tax revenues and get rid of the oil economy. With regard to the heavier weight of the positive effects than the negative effects of the variables involved, it is concluded that the implementation of this policy as a whole can be beneficial for the Iranian economy if the increased revenues from the increase in the payroll tax rate are properly managed. The policy of whether or not to increase the payroll tax rate depends on the macroeconomic conditions of the country. In the current situation of Iran's economy, given the negative economic growth in recent years, on the one hand, and the realization of 100% tax revenues and even above the forecast, on the other hand, it seems that the government should postpone the implementation of the increase in the wage tax rate, so that the economy can recover in terms of production and achieve positive and continuous growth.

Political and social stability is an important component of optimum management in the public sector economy and, in turn, a key element in good governance. This key component of good governance and the basic element of optimum management of the public sector economy have a significant relationship with education and health in different societies. At the same time, education and health are fundamental elements for creating human capital and human development. Political and social stability provides a pacific environment for economic progress. This is because these elements encompass the conditions under which the law is ruling, sufficient security is prevailing in different societies, and economic activists benefit from enough freedom. As social and political stabilities are not separable, they are used interchangeably in this article, and, for brevity, they are referred to as political stability. In other words, political stability in this article means political-social stability. Not surprisingly, countries that benefit from more political and social stability do possess more economic progress. As there is a significant relationship between political and social stability on one hand and human development on the other, reinforcing human development and human capital can have an influential role in promoting political and social stability. Consequently, governments can redirect their welfare expenditures to improve health and education that eventually provide enough ground for better political and social stability. Accordingly, one main goal of this article is to investigate the impact of public expenditure in education and health on political and social stability.

By using econometric and statistical methods, this study analyzes the factors affecting political and social stability through human development. It investigates the impact of public expenditure on welfare (especially those expenditures devoted to health and education) and political and social stability for selected countries. The selected countries include 34 developed countries, so-called OECD countries on one hand and 17 Middle Easten and North African countries, so-called MENA member countries. The MENA countries include Iran as well. The time period for this study is 1998 through 2020. By using a simultaneous equation system, this article explores the outcome of public expenditure in health and education on political and social stability in the mentioned countries. Moreover, and for a more realistic analysis, the other variables which influence political and social stability are addressed too. These variables include inflation rate, unemployment rate, inequality, and per capita income. Meanwhile, the role of democracy is discussed. For more scrutiny in this work, the negative correlation of investment and property rights is taken into consideration in the final analysis. Before econometric analysis, the dependency of some of the above variables on one hand and the political stability on the other are investigated statistically.

The result of the analysis in this study stresses some basic issues. It firstly, indicates that there is a positive and significant relationship between the welfare expenditures of the government, especially those dedicated to health and education, and political stability. Secondly, inflation rate, unemployment rate and inequality have negative and significant relationships with political stability. This paper presents the claims of new public sector theories versus the old public sector theories. The former claim is that the role of investing in health and education on political stability is much greater than concentrating on military power and security-oriented power to create political stability. According to the old theories of the public sector, however, the military power and concentrating on security orientations create political stability.

The significant relationship of the welfare expenditure of government devoted to health and education with political stability is the main finding of this research. The negative relationship of inflation and unemployment with political stability is another paramount finding of this work. By taking into consideration the first finding of this article, governments can improve health and education and create a significant amount of political stability. Also, by targeting a low inflation rate and decreasing the unemployment rate, they can promote the political and social stability. They can eventually boost the welfare of their citizens in the long run.

After making economic theories, the main goal of researchers in economics is to measure economic relations more accurately. For this purpose, various methods are used in economics to provide a better insight into the functions of economics. The evolution of knowledge in different approaches and methods of measuring economic relations is, thus, happening very fast.After the US withdrawal from the Barjam nuclear deal between Iran and the P5 + 1 countries in early 2018, relatively long turbulent waves occurred in the Iranian foreign exchange market. The overflow of these turbulent waves, in a short time, disturbed some markets, including financial markets, gold, currency and housing. The stock market, as a major financial market in Iran, did not show strong evidence of currency turbulence overflow at the beginning of these developments. Gradually, over time, the growth of the average stock market index along with the stagnation of transactions in a market such as the housing market showed the possibility of a long-term relationship between foreign exchange market movements and the stock market. The existence of empirical and accurate knowledge of such relationships leads to improved turbulence control by stabilizing the country's financial markets. On the other hand, the development of Iran's economy depends on improving the efficiency of financial markets, which necessitates such knowledge. The short-term relationship between the foreign exchange market and the stock market does not pose a problem in terms of financial theories. However, the long-run relationship, referred to in the economic literature as co-integration, is at odds with Market Efficient Hypothesis. This hypothesis states that dealers in the so-called markets behave rational and use all available information to discover the future trend of stock prices. Hence, stock price movement is random, and the long-term relationship between the foreign exchange market and the stock market violates the Efficient Market Hypothesis; such a relationship can be used for future stock market trends.

In financial economics, the co-integration of non-stationery variables is very important. This is because, despite the unpredictability of certain time series, their linear composition is predictable and can be deduced through standard methods. The empirical results suggest that the relationship between the exchange market and the stock market is inconsistent. Various factors lead to such a contradiction addressed in the present study. Here, using some empirical facts about unconditional distribution of financial data, a new Bayesian Method which involves the Partial Bayesian Residual-based Test is introduced and applied. This approach was proposed as an alternative to classical testing methods so as to estimate long-term parameters. There are also alternative methods to the OLS method, which provides only one co-integration relationship. These alternatives offer a consistent and efficient estimate of the long-run relationship. In this case, we can refer to the Dynamic Ordinary Least Squares method (DOLS) and the Fully Modified Ordinary Least Squares method (FMOLS), which were proposed by Stock and Watson (1993) and Phillips and Hansen (1990), respectively. In the present investigation, the FMOLS method has been used to make an efficient estimate of the regression coefficients of the long-run relationship, Inder (1993) used Monte Carlo simulations to show that the estimation of the long-run relationship using the FMOLS method is more appropriate than the OLS method, especially in large samples. This is because the bias of the parameter estimation reduces in long-run relationship significantly. It leads to the creation of residuals that more accurately reflect the structure of their generating process, which is very effective in the performance of the Partial Bayesian Test used in this study; the financial data are not normally distributed, contrary to the classical approach of co-integration tests. This study uses a Residual-based Co-integration Test that explains the behavior of financial data more accurately than a normal distribution approach. It is worth mentioning that this test considers the mentioned test as a special case of normal distribution. In this respect, it has a more general preference for modeling in our investigation.

The test was conducted using simulated data in different simulation quantities for two processes. The results confirmed the existence of co-integration between these two processes. It is worth noting that, to estimate the posterior distribution of the parameters of a Bayesian model, it is necessary to calculate the Marginal Likelihood Function of the parameters obtained through integration. However, when the Bayesian model has no mixed-scale normal distributions based on that inference Bayesian model, the integral cannot solve the problem by using analytical methods. In this case, a method such as the MCMC (Markov Chain Monte Carlo) Simulation must be used. Since the correlation hypothesis test in this study was not a co-integrated vector, the MCMC method was used to estimate the real exchange rate and the stock price data. The test results obtained with the Partial Bayesian method show a positive long-run relationship between exchange rates and stock prices. The indication of a co-integration between the stock market and the foreign exchange market means that the future trends of the stock market in combination with the foreign exchange market are predictable.

Based on the results, the long-run relationship between the exchange rate and the stock price index is positive. It is indicated that a one-unit increase in the exchange rate will lead to a 2.5-unit increase in the stock price index. This means that a linear combination of stock prices with the exchange rate is predictable and, thus, contradictive of the Efficient Markets Hypothesis about the stock market in Iran. In other words, the Efficient Markets Hypothesis about the Iranian stock market is rejected.

One of the important aspects of foreign exchange policy is the Central Bank intervention in the foreign exchange market. The Central Bank intervenes to stabilize the foreign exchange market by changing its foreign reserves. Governments prefer to keep the exchange rate stable because any sudden fluctuation can destroy the confidence of economic actors in the market and harm the financial market and the market for physical goods. In this regard, an important method of analyzing the behavior of Central Bank officials to control and manage the foreign exchange market is to estimate the reaction function and identify the factors affecting foreign exchange interventions of the bank. Knowing about the factors affecting foreign exchange interventions helps to forecast the next interventions of the Central Bank and gives economic actors a better understanding of the behavior and decisions of policymakers and their effects on financial markets and macroeconomic variables. In this study, a Mixed Frequency Data Sampling Model (MIDAS) has been used to investigate the factors affecting the foreign exchange interventions of the Central Bank. This method deals with the high-frequency variables as independent variables next to the low-frequency dependent variable. The frequency of the dependent variable must always be less than the frequency of the independent variable(s). Therefore, the Midas approach can use the maximum amount of information gained from high-frequency series. Better prediction is also made for the dependent variable. In this research, the data related to the years 2002 to 2018 were used to estimate the reaction function of foreign exchange interventions by the Central Bank. This was done with the variables of direct foreign exchange interventions (annual), the level of foreign exchange reserves (seasonal), oil and gas exports (seasonal), and exchange rate fluctuations (seasonal). As the results showed, among the studied variables, the rate of policy-making intervention was more sensitive to the amount of export. Also, with an increase in oil exports, the Central Bank's intervention in the foreign exchange market increases. In the period under review, the central bank interventions were mostly leaning-against–the-wind. In addition, the three methods of weighting Almon, Beta, and Exponential Almon were used to compare the performance of the variables to predict foreign exchange interventions of the Central Bank. In order to compare the performance of individual forecasts and the combination of forecasts, the mean squared error rank method was used. As the results showed, the combination of forecasts did not provide better performance than individual forecasts. Therefore, the individual estimates of foreign exchange interventions are highly valid. Through examining the reaction function of the Central Bank of Iran interventions, one can observe the irregular behavior of monetary authorities in the face of different market conditions. The interventions of the Central Bank in Iran obey no specific rules, and the foreign exchange policymakers intervene in the foreign exchange market in a completely discretionary manner, without considering a specific pattern for intervention. Although this form of intervention in periods of abundant foreign exchange earnings has been able to stabilize the exchange rate to some extent, with a decline in the foreign exchange earnings and foreign reserves, the power of the monetary authorities to manage the exchange market has diminished and the exchange rate has jumped to adapt to the realities of the economy. Therefore, it seems necessary for the Central Bank to regulate the method of foreign exchange interventions. The necessary condition is to synchronize the growth of liquidity in Iran with global liquidity and prevent its incompatible growth with the principles of the domestic economy. In fact, one of the most important prerequisites for successful foreign exchange market management is to control the unbridled growth of liquidity. In this case, we can hope for the success and effectiveness of foreign exchange interventions. The management of foreign exchange resources during periods of boom and bust of oil revenues is of particular importance too. The government’s injection of surplus foreign exchange earnings into the foreign exchange reserves will enable the Central Bank to use the resources accumulated in the accounts to manage the foreign exchange market in the event of oil shocks and foreign exchange earnings decline. This policy will help to prevent exchange rate fluctuations due to oil fluctuations. Derivatives can also be used as an alternative to cash market intervention. The advantage of derivatives is that their use does not necessarily change the country's foreign exchange reserves, nor does it overshadow the monetary policies. Therefore, the bank can change the exchange rate or prevent fluctuations by issuing derivatives without affecting the monetary basis.

 Income inequality and the role of redistribution policies are major issues in economics and politics. In the literature on the economic public sector, income distribution is introduced as one of the effective factors in changing the government spending. According to the median voter model, the government bases the supply of public goods and services on the demand of the median voter to meet the demands of the majority of citizens. In this regard, the median voter theorem states an optimal solution for the determination of the public goods level based on what the median individual prefers in a democratic system along with the majority voting rule (Atkinson and Stiglitz, 1980). According to the median voter theory, the government expenditure is affected by median voter preferences, and certain economic policies are selected to maximize the median voter utility; whereby the optimum level of public goods is determined (Dadgar, 2013). In the framework of median voter model, Hindriks and Myles (2006) suggest that a decrease in the median voter income to the society income average means an increase of inequality in the society and a raise in the demand for public goods and services. Accordingly, government expenditures are increased to satisfy the utility of most people; as a result, the government size grows. This proposes the hypothesis of the effect of inequality on the government expenditures. It is an important issue for some reasons. First, the government expenditure plays a major role in the implementation of fiscal policies which seek income equality in terms of distribution and stability. Thus, the income inequality influences the fiscal policy performance through the government expenditures. Second, the government paya attention to citizens’ demands due to political factors, which brings desirable consequences such as upgraded local managers and the continuity of current state activities (Zhang, 2020). Concerning the importance of such a discussion, this paper seeks to examine the effect of income inequality on the government expenditures in Iran’s provinces and to answer the question whether increasing income inequality is a source of government growth at a local level.        In order to empirically test the effect of income distribution on public spending in Iran’s provinces, an econometrics model based on panel data is considered as follows: In this equation, the public expenditures of a province per capita (  ) (including the current and construction expenditures in terms of million Rials) and the corresponding Gini coefficient, which represents the inequality of income distribution, are dependent and explanatory variables, respectively. The other explanatory variables are the province’s gross domestic production per capita ( ) (at current prices in terms of million rials), the province’s tax revenues per capita (in terms of million Rials) ( ), and the share of the province’s income from oil revenues (per capita in terms of million Rials) ( ), which is considered as the intergovernmental grant (from the central government to the provincial government). Also, indicates the disturbance of the model, and i and t are the sections (32 provinces) and time (during the period of 2006-2018), respectively. This model uses the Generalized Method of Moment (GMM). The results of dynamic panel estimation using the Generalized moments method (GMM) show that an increase in the income inequality leads to a raise  in the government expenditures in the provinces of the country. Also, lagged provincial expenditures, provincial GDP and intergovernmental grants (from the central to provincial governments) have positive and significant effects on public expenditures at the provincial level. The research’s findings are in line with the political model of government growth that emphasizes the positive relationship between income inequality and government expenditures. According to it, a raise of inequality increases the citizen’s demand for public goods and eliminates inequalities. In these conditions, the government is inclined to increase its expenditures that are effective in the improvement of its political position and attraction of citizen’s satisfaction. Increase of income inequality causes poverty and class gap in the society, which shows the inefficiency of government distribution policies. There are various reasons for the increase of the government expenditures and the public sector growth suggested by Hindriks and Myles (2006) in the context of a political model. The model shows that the distribution of income predisposes the government growth. From the point of view of public policies, inequality forces the government to spend on public goods and services to meet the people demand. This finding is in line with the political theory of government growth that emphasizes an increased inequality leads to bigger government; individuals that face inequality and poverty have more demand for public goods. Thus, the increasing of the government expenditures is supported by so many people; the government increases its spending in order to satisfy most people. This justifies the increase of public expenditures with the aim of satisfying the public preferences.

Nowadays, urbanization, which is closely related to economic development and industrialization, has become one of the driving forces of energy demand. The most prominent feature of urbanization is the physical growth of urban areas. This phenomenon has become an important social process in the 21st century, especially in many developing countries such as OPEC. The acceleration of urbanization leads to an increasing contradiction between economic growth and environmental development. The process of urbanization not only involves a large number of rural people moving to cities but also involves economic transformation and improvement of the industrial structure, which inevitably leads to the creation of urban infrastructures with large investments. Thus, it increases energy consumption (Liu and Peng, 2018). Although extensive research has been carried out on the relationship between urbanization and energy consumption, there are few studies about the OPEC countries.  Many studies have shown that urbanization can affect energy consumption or energy intensity through several channels. First, urban infrastructure must consume more energy through the expansion of economic activities. This is because urbanization leads to a shift from traditional agriculture with little energy consumption to industrial manufacturing with more consumption. Second, modern buildings need more energy (such as for air conditioners and elevators). Third, in cities, motor vehicles consume a large value of energy (Bloomi and Al-Shari, 2017).At the same time, new technologies (for example, energy-saving urban buildings, efficient household appliances, district heating systems, and energy-efficient transportation) reduce energy consumption in buildings and transportation in large cities.In addition, according to Tubler's law of geography, geographical locations are interdependent, and nearby places are more affected than distant places. So, according to the econometric literature, ignoring the space dimension in modeling causes errors in estimation and statistical inference (Seif and Hamidi Zari, 2017). In other words, although energy consumption varies among OPEC member countries, they may be spatially dependent due to geographical proximity, socio-economic interactions and common shocks, such as production technology and energy consumption patterns. This study examines the direct and indirect effects of urbanization on energy consumption.Since spatial interactions are the focus of this research and there are spatial interactions between urbanization and energy consumption, a simple econometric model cannot account for the impacts of spatial factors on energy consumption. Therefore, the research model is taken from the study of Sheng et al. (2018) and business variables, government expenditures and the space panel method are added to it.Urbanization may also affect energy consumption in suburban areas, which involves potential spatial (or indirect) effects of energy consumption on urban areas. The present study examines the effects of urbanization on energy consumption using random regression of effects on population, wealth and technology (STIRPAT) in a selection of OPEC member countries. In this regard, the space panel model and time series data during the period 1990-2020 have been used. The variables of trade, population, GDP, technology, total energy consumption and urbanization are extracted from the World Bank database. Based on the results of model estimation, the relationship between trade and energy consumption in OPEC member countries is negative and significant. Open trade allows developing economies to import advanced technologies from developed economies. The use of advanced technology reduces energy intensity. This process is called technical effect.Government spending also has a significant negative impact on energy consumption. Over the past decades, the allocation of energy subsidies has led to its excessive consumption in OPEC member countries. But recently, with increasing government spending and budget deficit problems, governments have adopted contractionary fiscal policies. The elimination of energy carrier subsidies is one of the plans to improve the budget, which has led to higher energy prices and lower demand.Industrialization has a positive and significant relationship with energy consumption in OPEC member countries. Given the role and importance of energy in the production of various industries, it can be said that energy has a very large share in industrialization. Industrial activities, such as high-tech production, consume more energy than agricultural production. According to the findings, with the long-term direct effects of industrialization variables, trade and economic growth have positive effects, whereas urbanization and government spending have negative effects on energy consumption. The results of indirect effects indicate the positive impacts of urbanization, trade and government spending and the negative impacts of industrialization and economic growth on energy consumption. The total effects of urbanization, industrialization and trade on energy consumption are positive, and economic growth and government spending have negative effects on energy consumption. Accordingly, it is suggested for in the OPEC member countries, to consider the effects of the spatial spillover of energy consumption to control it.

Development is a concept that simultaneously implies the change of multiple structures in various aspects of social life and requires a multidimensional process that pursues multi-species goals. Goals change with the introduction of new social variables and needs and increase the responsibilities of development managers. Development has ensured the efforts of a society to achieve its value goals, and its sustainability depends on providing relative welfare, complete security and sufficient awareness for all its members. In fact, sustainable development requires social justice and balanced attention to the cultural, political and economic aspects of the society. This should be done in such a way as to make the human resource development process hopeful.Development and justice are among the concepts whose legitimacy cannot be doubted. Justice and its position and relationship with economic performance have been explored in the literature of development economics. Over the past four decades, the theoretical and empirical areas of development have witnessed the growing intertwining of national development issues and scientific advancement in social justice. Thus, in the current situation, the relationship between social justice and national development is explained as an organic relationship. Fairness of conditions is an important variable that determines the desired economic performance. The purpose of this study is to study multidimensional poverty in Iran as an indicator of equitable development. A review of successful development experiences shows that they have a wise approach to designing development plans that are consistent with social justice. Therefore, in this study, the concept of equitable development is studied first, and then the multidimensional poverty index is calculated. Since poverty is a multifaceted phenomenon, the study of all its aspects and dimensions requires accurate knowledge. The Alkire and Foster method is one of the most widely used ways of calculating multidimensional poverty. It has also been used by the United Nations to introduce a multidimensional global poverty index. In this study, the index is examined in the five dimensions of education, health, employment, housing and standard of living.Considering the same weight for each dimension and the same weight for each of the indicators within each dimension, poor households have been found to be deprived of more than one third of the indicators. Then, after the identification of the poor people, Alkier and Foster poverty indices have been calculated using the raw cost-income data of urban and rural households in Iran during the years 1990 to 2020. Calculating the multidimensional poverty index shows that multidimensional poverty has been reduced in urban and rural areas of Iran. Of course, the intensity of this decrease is significantly higher in rural areas. The value of this index in rural areas has decreased from 0.483 in 1990 to 0.183 in 2014. This reduction is a reduction in the extent and severity of multidimensional poverty in rural areas during the years 1990-2020, which can be due to the living facilities provided to rural households in the post-revolutionary years.However, the decline in this index is not very obvious for urban households because most urban households had access to these amenities during the period. The value of this index for urban households in 1991 was equal to 0.239, which was the highest rate during the years 1990 to 2004. After that, during the years 2004-2009, there was a fluctuating trend. During these years, this index was 0.260 in 2003 and 0.294 in 2007, which was the highest value of the multidimensional poverty index during the studied years. This can be due to the high inflation and the recession in the late 2001. Nowadays, the multidimensional poverty index is reported in global databases as a development index, so it can be a criterion for policymakers to make comparisons between Iran and other countries. It introduces equitable development not only in income poverty but also in the deprivation of the poor minorities and marginalized groups of equitable access to various aspects of quality and prosperous life. It brings multidimensional poverty into focus by defining equitable development. Therefore, in order to promote development based on justice in a society, conditions must be created for equal opportunities and access to resources such as education, health, employment and living standards.

The extremely poor population (less than $ 1.9 daily income) has declined in the last three decades (World Bank, 2020), but more than 600 million people still suffer from severe poverty. Crises like the outbreak of the Covid-19 make the poverty even worse. Iran, as a middle-income country, has experienced a reduction in poverty in recent decades, but economic crises such as the stagflation in 2018 have increased the number of the poor.The importance of poverty (and, of course, inequality) has brought the issue into the focus of politics and science, creating an extensive literature. To understand the nature and determinants of poverty and the ways to deal with it, many theories are introduced to pave the way for policy-making. Measuring poverty and drawing its map are the first step in the study and policy-making of it. Measuring poverty is impossible without defining it. Since the nineteenth century, when empirical research in the field of poverty began in England, the definition has undergone significant changes. Poverty was initially defined as an income below a poverty line, but, in the 1980s, the concept of multidimensional poverty was introduced and used as an alternative to income poverty. Along with conceptual developments, technical advances in the measurement of poverty have been made in both income and multidimensional poverty areas. In recent decades, these issues have spread in Iran, and various approaches have been used to measure poverty. In this regard, the present study measures multidimensional poverty in the urban areas of Iran.

In this study, the Alkire-Foster (AF) method is used to measure multidimensional poverty. By this method, the identification stage is done in two steps, determining the level of deprivation and identifying the poor. Each of these steps has its own cutoff, which is why it is called the "dual cutoff method". The aggregation stage is done with special indices of this method. Calculating the indices requires three parameters including the dimensional deprivation cutoff vector, the indicators weight vector, and the poverty threshold. The weight of the indicators can be measured in four ways: 1) equal weight, 2) the views of experts or policy makers 3) participatory approach according to the priorities of the community and 4) statistical methods. In this study, the statistical method used for weighting is Multiple Corresponding Analysis (MCA).MCA can be categorized under factorial methods that are formed around the concept of inertia and variance. The factorial approach has three important subsets: principal component analysis (PCA), factor analysis (FA), and MCA. As an intuitive description, PCA can be thought of as fitting an ellipsoid to a mass of n points in the d dimensional space, as the obtained elliptical diameters are the new axes. These axes are called the "principal component." Despite the advantages, the PCA method has its limitations. Among other things, this method is designed for numerical variables with the same scale. For ordinal categorical variables, the MCA method was developed as an extension of the Correspondence Analysis (CA) method.

As many as 13 indicators are selected in the four dimensions of "economic welfare", "housing", "health", and "education" with the data of the Household Expenditure and Income Survey in Iranian urban areas from 2004 to 2019. The calculation of the indicator weights by MCA is the first step. One of the factors affecting the weight of an indicator is the diffusion of that trait between households. Indicators with very low deprivation take higher weights. This feature is called the "prevalence principle". To implement the AF method, the poverty line corresponding to the headcount ratio of 30% is considered, which is equal to 0.209. Using the weights of households (i.e., the number of the households), average deprivation share across the poor and the adjusted headcount ratio in the whole sample are found to be 34.12 and 10.60 percent, respectively. After the calculation of the annual trend of the multidimensional poverty index, it emerges that this trend is downward and convex overall, but, in the last two years of the period, the headcount and the adjusted headcount ratio increase. Robustness analysis and statistical inference confirm these results. The study of regional poverty shows that Mazandaran and Sistan and Baluchestan have the lowest and the highest headcount and adjusted headcount ratios, respectively.To compare the effects of the weighting method on the results, the poverty indices are calculated in terms of MCA, equal, and nested weights with a poverty line of k = 1/3. The headcount indices of these three methods are 0.13, 0.20, and 0.29 percent, respectively. Also, the weights obtained from MCA achieve lower indices. The analysis of the contribution of the indicators in the adjusted headcount ratio of the whole sample indicates that "the education level of the household head", "communication facilities", and "income poverty" have the highest contribution.

The downward and convex trend of annual indices means that, over time, poverty reduction occurs at a slower slope and, finally in the last two years, poverty indices have an upward slope. Of course, this coincides with the stagflation in the Iranian economy. The examination of the deprivation trend in the indicators also shows that the indicators of "economic poverty", "calorie adequacy", "household literacy index", and "the education level of the household head" are upward. Meanwhile, the contribution of the first two indicators in terms of the adjusted headcount index in the period under study is increasing. In other words, in the last two years of this period, the indicators of both multidimensional and income poverty increased, which requires policymakers to pay attention to this issue. Specific policies should also be developed and implemented for areas and groups that are more impoverished.