فصلنامه پژوهشهای اقتصادی (رشد و توسعه پایدار)
سال بیست و سوم شماره 4 (زمستان 1402)

Technology provides an opportunity for the economy to move from polluting sources to renewable sources to meet energy needs. Increasing economic complexity means more use of technology and innovation in production and may cause the expansion of effective technological products such as renewable energy. In the past few decades, the share of renewable energy has increased due to a wide range of factors, such as government regulations to promote the use of renewable energy, reduction in the cost of installing renewable energy and increasing production capacity, oil price fluctuations, and the positive effects of renewable energy in reducing emissions. Carbon and innovation processes have increased in the energy sector. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019.

In dynamic models, due to the presence of a lagged dependent variable, OLS or GLS methods cannot be used to estimate the model, because the disturbance components are correlated with the lagged dependent variable, and the estimation results are biased and inconsistent as before. Therefore, to solve this problem, the GMM method proposed by Arellano and Bond (1991) is used. The GMM estimator belongs to the set of instrumental variables’ estimators. In this method, in addition to solve the problem of the correlation of the independent variable with disturbance components, the endogeneity of the variables and the heteroscedasticity of the variances are also removed. It should be noted that this method is applicable when T (number of periods) is smaller than N (number of sections).

The results show that the economic complexity index has a negative and significant effect on carbon dioxide emissions in developing countries. Variables such as trade openness and energy intensity increase carbon dioxide emissions, and the Kuznets curve hypothesis is confirmed for developing countries, and economic complexity leads to an upward movement of the Kuznets curve. Renewable energy consumption has a significant effect on reducing carbon dioxide emissions, and also at higher levels of economic complexity, renewable energy consumption causes a greater reduction in carbon dioxide emissions.
Conclusion and

The need for a more accurate understanding of economic phenomena has prompted economists to review previous theories and present new theories that have a new window to economic development literature. The goal of all countries is to achieve sustainable economic growth and development. Renewable energy technologies are promising, but there is very little information about its role as a limiting factor in reducing environmental pollution, especially in developing countries. Therefore, in this research, the effects of renewable energy consumption and economic complexity as well as their mutual effects on environmental pollution have been investigated using the GMM method in developing countries over the period 2000-2019. The results show that the economic complexity index has a negative and significant effect on the emission of carbon dioxide, so it can be said that for developing countries, moving towards a more knowledge-oriented economy can improve the quality of the environment. The variables of trade openness, energy intensity significantly affect positively CO2 emissions. The EKC hypothesis was confirmed with the positive logarithm of GDP per capita and its negative square coefficient. According to the results of the study, economic complexity in countries under study leads to an upward movement of EKC, which means that as economic complexity increases in developing countries due to increased energy demand, scale effects occur and lead to higher CO2 emissions.
In this study, energy intensity has a positive effect on the increase in carbon dioxide emissions and as a result the increase in environmental pollution in developing countries.
The specific result of this article is the significant effect of renewable energy consumption on the reduction of carbon dioxide emissions in developing countries. At higher levels of economic complexity, renewable energy consumption causes a greater reduction in CO2 emissions. In terms of the role of complexity, it can be argued that in countries under consideration, the share of renewable energy should be significantly increased by using innovation processes in the energy sector. Considering the negative effects of the share of renewable energies on carbon dioxide emissions per capita, it is suggested to define new patterns of energy consumption by relying on renewable energies in development programs and using incentive tools to replace renewable energies instead of fossil fuels to reduce pollution. Developing countries should support knowledge-based industries, increase the import and production of environmentally friendly technologies, and increase the share of renewable energy in their plans to protect the environment. In addition, pricing strategies can be proposed to avoid increased fossil fuel consumption.

During the last two decades, with the increase in international exchange of goods and services, environmental problems, including climate change and global pollution, have increased significantly. The global effort to reduce environmental problems has put the importance of production and international trade of environmental goods on the agenda of many developed and developing countries.

Institutional restrictions influence trade and export of these goods. These restrictions include environmental regulations, quality of regulations and rule of law. The aim of the present study is to investigate the effect of this category of institutional restrictions on the export of pollution management goods in developing countries in the framework of the gravity model. In this article, the environmental goods under study include those goods, which are produced or consumed by industry in order to reduce and manage air and water pollution. The econometric model is estimated by panel data for period 1996-2021 and a sample of 131 developing countries, and 196 export destinations using the fixed effects method.

The results show that the institutional limitation from the perspective of strict environmental regulations and the quality of the institutional environment of the countries of origin has an effect on the export of environmental goods that manage pollution. This result is also true from the point of view of strict environmental regulations of export destinations. Therefore, in addition to the traditional factors affecting international trade, institutional restrictions are strong drivers of the export of pollution management goods in developing countries and their export destinations.

Therefore, policies based on institutional restrictions from the perspective of strict environmental regulations in developing and destination countries help the export flow of environmental goods that manage pollution and lay the foundation for the participation of developing countries in the global and regional value chain of environmental goods.

The purpose of this study is to investigate the effect of oil price shocks on the components of the Iranian labor market and the role of government capital expenditure in this field. Labor market components include job vacancies, job finding rates, inflow rates to unemployment and unemployment rates. For this purpose, the structural vector autoregressive approach over the period 2005:2- 2019:3 has been used. The results of impulse response functions show that positive oil price shocks have significant effects on model variables. However, negative oil price shocks are not significant. The positive oil price shock increase government capital expenditure, but due to the inefficiency of government investment, job vacancies decrease and the inflow rates to unemployment increase. As a result, the unemployment rate has risen in response to positive oil price shocks. The results show the Dutch disease and the asymmetric effect of oil price shocks on the labor market.

In addition to creating economic problems, the problem of unemployment can be the source of behavioral disorders and political tensions and can be considered a threat to the health of a society. For this reason, analyzing the labor market and knowing the factors that lead to unemployment is one of the concerns of every economy. Oil is a source of income in exporting countries and an important production factor in importing countries. Therefore, oil price shocks are expected to have an impact on market developments in terms of income and cost effects. This study aims to answer the question of whether oil price shocks have an effect on the components of Iran's labor market. For this purpose, the effect of oil price shocks from the channel of construction expenditure on the rates of finding a job, entering unemployment, unemployment and job opportunities, which are adjustment factors and represent the components of the labor market, are investigated.

In this article, structural vector auto regression (SVAR) model is used to investigate the effect of oil price shock on labor market components. For this purpose, it is necessary to specify the VAR model first, and then analyze the SVAR model by applying restrictions on matrices A and B. Constraints are imposed on the relationships between the regression residuals and the disturbance terms of the structural equation system so that the structural form can be identified.

The results related to the significance of the variables show that all the variables are at the significance level. In addition, the optimal lag for estimating the basic VAR model based on the Akaike criterion is 1. Examining the roots of the VAR equation system shows that all the roots are less than one and are inside the unit circle, so the effects of shocks disappear in the long-run and the system is stable. The findings show that one standard deviation shock to the series of positive changes in oil price causes its instant increase by 0.4 and its effect decreases in the second season and disappears from the third season onwards. Government construction expenditure has increased immediately in response to shocks (one-time lag amounts), but this increase is not lasting, and it has declined in the second season, and in the third season it disappears with a slight increase in shock effects that shows a strong dependence on oil revenues. Because the only source of construction expenditure is from oil revenues, job openings have declined due to these shocks, which last until the second season. Then it increases slightly, but less than the initial negative effect, and gradually the shock effect disappears. One standard deviation shock to the series of negative oil price changes will cause it to increase by 0.1 immediately, and its effect will disappear in the third quarter. The effect of negative oil price shocks on any of the variables is not significant. However, these shocks immediately reduce government construction spending. This again shows the dependence of construction expenditure on oil revenues because at the time of the drop in oil prices, construction expenditure is decreased and allocated to current expenditure.

The aim of this study was to investigate the effect of oil price shocks on the labor market. For this purpose, the effects of positive and negative shocks of oil prices on construction expenditure, job opportunities, and unemployment rates, entering unemployment and finding jobs in a SVAR model were investigated. Positive (negative) shocks in oil prices immediately increase government construction spending. This increase (decrease) is not lasting and quickly decreases (increase) and from the third season onwards, the shock effects disappear. The positive shock of oil prices has a significant effect on four components of labor market, namely job opportunities, entering unemployment, job finding rate and unemployment rate. However, negative oil price shocks are not meaningful. Therefore, oil price shocks have asymmetric effects on the labor market. The results also confirm two problems of dependence on current expenditure and Dutch disease. Because shocks only affect the short term, while construction spending is expected to improve job opportunities in the long run.

The interactions of economies have caused the sensitivity to choose import sources, target markets and trade partners in general. Each country chooses its own trade partners based on its coordinates in order to minimize its import costs and generate maximum export income while avoiding the negative effects of international economic fluctuations. Diversification of trade partners is one of the ways to strengthen of an economy and reduce the vulnerability against international economic fluctuations and shocks. Diversification of import sources and export destinations of each country can lead to the stability of foreign trade and increase the stability of domestic production. In Iran's economy, due to the special conditions, such as economic sanctions, this issue is of double importance. In the previous periods of sanctions (before 2017), one of the weak points of Iran's economy has been the decrease in diversity in the mix of foreign trading partners, which includes the decrease in the number of buyers of oil (as Iran's main export product), the decrease in the arrival of foreign tourists, and the reduction of countries exporting goods to Iran. In this situation, two countries, China and Russia, became Iran's main trade partners, and to some extent, it reduced the impact of Western economic sanctions against Iran's economy. Meanwhile, in the last two decades, China has practically become the main competitor and substitute for the economic powers of the world, known as the OECD member countries, and has acquired large markets in South and East Asia, the Middle East and Africa. Therefore, it can be said that diversification of trade partners for all countries of the world practically means creating opportunities and for Iran, it means a way to survive.

The present research is based on the "Locomotive theory", which expresses the influence and effectiveness of the economic fluctuations of countries on each other through foreign trade. For this purpose, two models with the same structure were designed for two periods during 1970- 2018 to investigate the role of China's presence or absence among Iran's trading partners using the structural vector auto-regression (SVAR) model. According to the "Locomotive theory", international economic fluctuations affect countries through foreign trade, and only a few countries have the potential to bring countries out of the crisis. This theory states that during 1975-77, the United States was the main "locomotive" to pull out the world economy (more precisely, the industrialized countries) from the previous recession (the first oil shock), and paid a very high price for it, and it was necessary for America's major partners in that period, especially Japan and Germany, to accept their role as the locomotive of the world economy and in this way help both the American economy and the world economy. This theory specifically states that industrialized countries are the sources of international economic fluctuations and their prosperity or recession first spreads to major partners and with a delay to other countries.
The monetary and financial policies of the United States have played a decisive role in the development of global economic cycles through trade and financial links with smaller countries. In recent decades, although the importance and role of the United States has remained, but the US economy is not growing fast enough to act as the sole locomotive of the world economy train, especially in the last decade. China alone, and other major emerging markets as a whole, have become important drivers of the global economy. China and other major emerging markets are increasingly interdependent. Because on the one hand, China is the main importer of raw materials, and on the other hand, it is a supplier of manufactured products and foreign investment. The occurrence of such a phenomenon in the field of international economy has attracted the attention of many researchers to discuss the role of business partners and examine the unilateral and mutual effects of such decisions.
According to a study conducted in 2015 by Assoumou Ella for Kenya, the trade relationship between a third world country and industrialized countries is drawn in the presence of an emerging economy. In this research, the same model is used for Iran's economy. For this purpose, in the present study, based on the theoretical and experimental literature of this field a structural vector auto-regression (SVAR) model has been designed and specified. The first reason for using this model is its design based on the theoretical structure, and second reason is to provide a framework in which a variable, while being endogenous, is affected by other endogenous variables; but it should not affect them. The second case is very important regarding Iran's economy; because the macroeconomic variables of Iran's economy for several reasons (weak structure of Iran's economy, the issue of sanctions, customs tariffs) have no significant effects on the macroeconomic variables of trading partners included in the model.

The results of the analysis of the reaction functions show that in most cases, the fluctuations of the macroeconomic variables of Iran (including GDP, inflation, FDI, export and import) have decreased in response to the fluctuations of GDP and inflation of OECD countries after the inclusion of China in the model. So that the intensity of the impact of the shocks entered into the model has become milder and the time for disappearing of the shocks has also been shortened.

The results show that the diversification of Iran's Trade partners during the mentioned period has reduced the effect of the economic fluctuations of OECD countries on the macroeconomic variables of Iran. This means more stability of Iran's economy, so diversification of trade partners leads to resiliency against international crises, especially in the context of sanctions.

One tool to achieve macroeconomic goals is to control the volume of liquidity. There are two views on the control of liquidity volume. The first view argues that good governance and commitment to the laws for money creation hinder increasing  and uncontrollable volume of money. This view emphasizes the important role of institutions in controlling or growing liquidity. So, one of the reasons for the growth of liquidity is rooted in the laws and the extent of the rule of law of the countries. The second view suggests how the creation of money affects the rule of law and its influence channels. Long-term mismanagement of money has sudden and unpredictable effects and leads to institutional and sometimes fundamental change. The purpose of this article is to explain the non-linear relationship between money creation and the rule of law. For this purpose, the panel model with a threshold approach (PSTR) has been used, based on the data of the countries having oil reserves during 2002-2020. Based on the results, the variables of money creation and rule of law have negative relationships with each other, and the results confirm the acceptance of both views. In other words, the creation of money and its consequences changes and weaken the rule of law through various channels. Also, the weakness of laws in oil countries leads to the growth of money creation. Therefore, one of the causes of the weakness of the rule of law in these areas should be sought in the creation of money and its consequences. Moreover, the growth of liquidity is affected by the weakness of the rule of law in the growth or control of the amount of liquidity.

In the early models of economic growth, the role of saving and investment was emphasized. In the next models, factors such as the growth of knowledge and technology, human skill and business growth were taken into consideration. In the last few decades, the role of non-economic factors such as democracy (Sen, 1999) and institutions (North, 1990; Acemoglu, 2004) on economic growth has been emphasized. Acemoglu et al. (2005) argue that the distribution of resources and the distribution of power have dominant effects on the growth path of countries precisely through their effect on economic institutions such as property rights (Hartwell, 2018). From this point of view, it is political institutions that affect economic variables.
On the other hand, extreme behavior by economic institutions, whether during or in the acceleration of a crisis, may in turn disrupt or determine political institutions and their subsequent paths and quickly change the status quo in a destabilizing manner. Periods of crisis and periods of severe inflation have the ability to impose changes in the distribution of power throughout society, and as a result, change political institutions. Even more "normal" economic disturbances may change bargaining strategies and political coalitions, and transform a country's political institutions (Hartwell, 2018). From this point of view, the economic institution of money will have an effect on political institutions (Money affects political institutions)
Based on this, the present study, while examining the relationship between money creation and the rule of law, and how these two affects each other, seeks to examine two perspectives. The first perspective believes that the rule of law prevents the expansion of the money supply. Therefore, the reason for the growth of liquidity should be investigated in the laws and the extent of rule of law. In other words, the weakness of the rule of law causes the growth of liquidity. Another perspective emphasizes the issue of money creation and its benefits and examines how money creation affects the rule of law and its influence channels. If we look at money as a receipt for production, it means that the people of a nation determine GDP by producing and creating wealth and receive a receipt in the form of money in return for their share in it. Next to this group, there is another group (governments and bankers) who have the power to create money (or those who are given money created by the choice of the government and banks) and when dividing GDP, next to the first group own part of the production. This is the effect of money creation on property rights and consequently on the rule of law.

In this research, the bilateral and non-linear relationship between money creation and the rule of law is investigated among selected oil-abundant countries during 2002-2020 by using the Panel Smooth Transition Regression Models (PSTR).
To investigate the mutual effects of rule of law and money creation, two models were considered. In the first model, the rule of law index was considered as a dependent variable, and in the second model, broad money growth (annual %) was considered as a dependent variable. Control variables according to previous studies include oil rents (% of GDP), economic growth (GDP growth), trade openness, urban population growth, quality of regulations and abundance of natural resources.

The linear part confirms the negative and one-way causality relationship from money creation to the rule of law. The estimation results of the non-linear part of the model confirm the existence of a negative relationship between money creation and the rule of law, and confirm the bilateral causality relationship between the two. In other words, the results show that the creation of money is a factor to weaken the rule of law and the weakness of the rule of law has also caused the growth of liquidity.

The results confirm the existence of a negative relationship between money creation and the rule of law, as well as the bilateral causality between these two variables. In other words, the results show that the creation of money and its benefits change and affect the rule of law through various channels. Also, the weakness of rule of law in oil countries leads to the growth of money creation. Based on the results, it is suggested that the oil governments provide space for investment and free trade by shrinking their bodies, and with commercial freedom and the development of financial markets, and by directing foreign exchange income and stray liquidity to the real sector of the economy in a targeted manner. It is also suggested that the oil countries manage their liquidity by reforming the monetary system and the banking sector, and defend private property and the rule of law by preventing the transfer of ownership that occurs through money creation and inflation. This can provide more opportunities for the private sector. The prosperity of the private sector and the increase of competition in different economic sectors and the use of economic freedom policies lead to more dynamism of the economy.

The return of the stock market is affected by several factors; although some of which are not economic, they strongly affect the financial markets. The Covid-19 epidemic is also among these factors that has severely affected the global economy, empathetically the financial markets. Therefore, considering the importance of this epidemic in the stock market, the current study evaluates the effects of the Covid-19 epidemic crisis on the stock return index of the financial markets of China, America, and France; besides, it examines its spillover effects on Iran. To investigate the contagion of turbulence and the direction of spillover from the mentioned countries to Iran, the weekly data of the stock return index available on the websites of the Iranian Stock Exchange have been used. Moreover, the stock exchange of foreign countries during two periods: before the outbreak of the Covid-19 epidemic (January 2018 to December 2019) and the time of the outbreak of the Covid-19 epidemic (January 2020 to December 2021) have been examined. Then Oxmetrics software was used to check the conditional correlation, and SPSS software was used to measure the stationarity and unconditional correlation.

The present research evaluates the spillover effects of the covid-19 epidemic on the stock return index of the financial markets of China, America, and France and examines the mutual relationship between the aforementioned countries and Iran using the weekly stock return data of Iran and foreign countries. It has been analyzed using (DCC-GARCH) and (CCC-GARCH) models.

In this article, αii represents the effects of arch in each of the variables' past period turbulences, and αij represents the effects of the shock of variable i on the current shock of variable j. This spillover effect is calculated as the square of the residuals arising from the forecasted yield patterns. Garch effects are considered as βii. In other words, βii shows the stability of the shock in each of the series.
ρij also expresses the conditional correlation between two variables, which provides a representation of their simultaneous movement. Of course, both terms αij and β can indicate the overflow between indicators, because the shock overflow effect is determined by non-diagonal values. In the constant conditional correlation model, coefficients αii and βii are significant. In other words, they represent the amount of shock transmission in the conditional shocks of countries' returns.

The results indicate that in the post-epidemic period, the Iranian stock market experienced a decrease in stock returns, which can be caused by factors such as the imposition of sanctions and the stagnation of economic activities in addition to the spread of Covid-19. Also, the collapse of the Iranian stock market, which occurred in August 2019, led to the confusion and pessimism of more and more investors and finally led to the withdrawal of capital from the stock market. In such an uncertain and chaotic atmosphere, the spread of Covid-19 also aggravated the existing conditions due to the restrictions and also the implementation of government quarantines. Also, the results show that at the moment of the outbreak of the Covid-19 virus, all the sample countries have faced a decrease in stock returns. During the covid-19 epidemic, the impact of the Iranian stock market on China has been greater than that of other studied countries, which is important because China and Iran are each other's trading partners. It should be mentioned that during this period due to restrictions on the borders, the relationship between Iran and China became prominent. Also, Iran's stock market is not strong enough to influence global financial markets including China, America and France.
The growth of the stock return index has been increasing during the four-year period (2018-2021) in China, America and France, however the stock return index of Iran has been decreasing. The growth of China's stock returns during this period has been higher than that in the other studied countries. Also, the stock return index of all sample countries has faced a decrease in the stock returns during the outbreak of Covid-19.

Pandemic diseases are an integral part of the history of human societies and their long-term effects have always been considered. The outbreak of the Covid-19 disease at the end of 2019 caused economists to investigate its economic effects using different models, which were usually based on partial equilibrium. In this study, with the motivation of understanding the effect of the spread of a pandemic disease and its policy responses on economic and health conditions, the dynamic stochastic general equilibrium model and the new Keynesian perspective have been used. Examining the impulse response functions of the variables to the health shock caused by the Covid-19 outbreak indicates a decrease in employment hours, production, consumption, investment, health status and an increase in inflation. In response to these conditions, the increase in public health expenditure leads to a faster convergence of macroeconomic variables to their steady-state values. According to the results of the simulation, it is suggested that the governments use the experiences related to the first wave of the disease outbreak and equip themselves with the necessary tools to use them during the temporary social quarantine (such as the ability to conduct tests on a large part of the population). The ability to identify infected people and impose personal quarantines instead of compulsory quarantines will reduce stagnation. Another solution to control a pandemic is to vaccinate the mass population to achieve herd immunity. All of these require increased public health spending.

The evidence and results of the studies indicate the profound effects of epidemics such as the Covid-19 disease on the economy of countries. In this study, with the motivation of understanding the effect of the spread of epidemic diseases (with an emphasis on the Covid-19) on the economy and the government's policy responses to the dynamics of the macroeconomic variables of Iran, a dynamic stochastic general equilibrium (DSGE) model and the New Keynesian (NK) perspective were used. Unlike computable general equilibrium models, DSGE models are in a random environment, and since the duration of the virus's spread and its impact on the economy are unknown, it is more appropriate to use DSGE models (Yang, Zhang and Chen, 2020). In order to achieve the goals of Jazer's studies, in the first step, a DSGE model based on NK was designed and the effect of an epidemic disease on the macroeconomic variables of Iran was simulated. The designed model was quantified with a three-month (seasonal) frequency and using the data of Iran's economy (2004:2-2021:1).

The results showed that increasing the risk of health disaster by one standard deviation gradually causes a decline in health status. After that, in order to improve the health status, the quarantine hours were increased, which means an increase in investment in health. On the other hand, since more hours are allocated to quarantine, the hours of employment will decrease and subsequently the final productivity of physical capital will decrease, which is due to the complementarity of labor and capital in Cobb-Douglas production function. Finally, labor income and capital income also decrease. Therefore, production, consumption, and investment fluctuate significantly, and this comes from the optimal choice of the household in the face of this impulse. As a result, as the health status declines and consumption declines, the level of well-being declines (like the result of Yang, Zhang, and Chen, 2020). Over time, the lack of physical capital causes an increase in physical investment and working hours, and finally they slowly return to their previous stable level. In the second step, by applying a change in the AR(1) equation of public health expenditure, the effect of the government's financial reaction on the macroeconomic variables of Iran's economy in the face of the health shock was evaluated. In the base scenario, the government has no intervention in the economy and the state of fiscal inactivity is considered for the government. In another scenario, the active presence of the government, or in other words, the design of discretionary financial policy, affects the economy.

The results showed that the design of a discretionary financial policy in the form of increasing public health expenditure in the context of an epidemic has led to a faster convergence of macroeconomic variables to their stable conditions. In justifying the results, it can be stated that in the face of the outbreak of an epidemic, with the increase in public health expenditure and the subsequent increase in quarantine hours, the employment hours have decreased less. On the other hand, the increase in public health expenditure and the subsequent improvement of health leads to an increase in the productivity of the labor force through the increase in the life expectancy of a person as well as the length of working life. This has led to an increase in household income, followed by an increase in the level of consumption and investment. Also, an increase in public health expenditure leads to an improvement in health status. As a general result, the government's financial reactions in the face of the impulse of an epidemic disease lead to a faster convergence of most variables to their stable conditions in the Iranian economy.

The lack of statistical data at the regional level has led to the expansion of non-statistical methods for the regionalization of national input-output tables. The main idea of the current research is the regionalization of national dynamic input-output tables using the extension of the Charm method. This research using this non-statistical method provides an estimate of the sectoral capital matrix in the regional level, and finally, with the help of the numerical index of capital productivity and the Williamson’ capital index and comparing it with the relative advantage index, it measures the capacity of capital formation. Part of it is in Isfahan province. The results show that the industry sector with the largest share of output from the total output of the province has the lowest numerical index of capital productivity and the highest balanced diffusion effects of capital and the highest comparative advantage in 2015.

One of the most efficient methods for examining intra-regional economic capacities is the use of intra-regional and inter-regional capital matrix. In Iran, due to the lack of sufficient statistical data, no attempt has been made to estimate the sectoral capital matrix in the regional level. The purpose of the current research is to regionalize the national dynamic input-output table with the help of expanding the CHARM non-statistical method and estimating the intra-regional and inter-regional capital matrix; to provide an analysis of the capital capacity of different economic sectors in the region with the help of these matrices. In the current research, among all the non-statistical regionalization methods of the national input-output tables, the Charm approach has been selected in accordance with the regional data. The reason for choosing Charm method is the existence of Cross Hauling in Isfahan province. One of the problems of Charm's method is the placement of national and regional technology coefficients. This simplifying assumption causes the intermediate demand within the region to increase and therefore the added value, which is estimated as a residual; it will be very small or even negative. For this purpose, the current research will regionalize the matrix of national technology coefficients with the help of spatial coefficients; to solve the problem. By estimating the regional capital matrix, an analysis of the final productivity of the sector's capital factor and inter-sector capital distribution will be presented, and the results of these sectors will be compared with the indicators of comparative advantage of the sector. Finally, the research questions will be answered:
Which effect will the adjustment of the national technology coefficients have on the added value of the province?
What is the capital matrix of the sector in Isfahan province?
Which sector in Isfahan province has the highest numerical index of capital productivity?
Which economic sectors in Isfahan province have more distribution of capital formation?
What are the economic sectors with the greatest comparative advantage in Isfahan province?

At first, it is necessary to estimate the national capital matrix with the help of available data and simplifying assumptions. By estimating the national dynamic input-output table, we will have an estimate of the regional dynamic input-output table with the help of the extension of Charm method. To solve the problem of equality of national and regional technology coefficients, by multiplying the diagonal matrix of spatial coefficients in the matrix of national technology coefficients, we will obtain the spatial technology matrix of the region, and by multiplying this estimated matrix in the resulting diagonal matrix, we will obtain the regional technology matrix. Therefore, smaller regional coefficients will be estimated.
On the other hand, to estimate the intra-regional capital matrix, the difference ratio of the region's output in two periods is used to the same amount at the national level. In this case, the intra-regional capital matrix is estimated. A time interval of one year is considered. The reason for choosing this time interval is that the country's budget is one year and a huge part of the inter-sectoral investment in the region is done by the central government. To estimate the intra-regional capital matrix, the spatial ratio of the region's capital asset ownership to the entire country is used. Finally, by subtracting the national capital matrix from the intra-regional capital matrix, we will get an estimate of the correct inter-regional capital matrix. Finally, with the estimation of the capital matrix, the assessment of the capital formation capacity of the intra-regional sector of Isfahan province is carried out with the help of single-factor productivity analysis of capital and the Williamson index of capital and the estimation of the relative advantage index.

In the case that the coefficients of national technology are equal to regional technology, the added value is negatively estimated in four sectors, agriculture, mining, water and electricity, gas and construction. This is despite the fact that in the proposed method of the current research, these positive values are estimated. According to the capital matrix, the most productions were related to the industry, construction and agriculture sectors. Also, the most capital purchases were related to industry, services and real estate sectors. The highest level of sector productivity is related to the communication, mining and transportation sectors. One of the reasons for the increase in user productivity((L↑)/K ) of the sector is compared to other economic sectors. According to Wilsamson's index, the industrial sector, as a supply sector, has distributed its produced capital goods in a more balanced way among the demand sectors. Three sectors, industry, transportation and real estate, have the greatest comparative advantage according to both indicators. But none of the sectors has a high relative advantage.

In summary, the results show that the industry sector with the largest share of output from the total output of the province had low productivity in 2015. Meanwhile, according to Williamson's index, this sector has the most balanced emission effects with other economic sectors, and the results of the previous link also confirm this. Also, based on the RCA and SRCA indices, this sector has a comparative advantage. Therefore, paying attention to new investment in this sector and improving production technology can have good effects on the sector itself and ultimately on other economic sectors in the region.

 In order to target the limited budgets of poverty alleviation programs and increase their efficiency, a wide range of targeting methods including means testing, proxy means testing, categorical targeting, geographical targeting, self-targeting, and community-based targeting has been used  in developing countries (Coady, Grosh and Hoddinott, 2004). However, targeting in Iran, in the best case, has been based on the proxy means testing. Kidd and Wylde (2011) have criticized this method due to lack of transparency and poor predictions in the field of identifying the poor. The main purpose of this article is to compare the different economic and social characteristics of Iran’s rural households with the aim of finding the best characteristics in order to target subsidies in Iran. In this context, the following questions are raised: In a situation where accurate information about household income or expenses is not available, how should households be prioritized to receive subsidies based on their characteristics? How much cash subsidy should each household receive in order to reduce the aggregate poverty? To answer these questions, by following, Kanbur (1987), Ravallion and Chao (1989), Elbers, Fujii, Lanjouw, Özler and Yin (2007), Glewwe (1992) and Araar and Luca (2019), I use a new numerical algorithm, which acts as optimal poverty group targeting. This method is conceived to find the optimal group transfers that allow the largest possible reduction in any additive poverty indexes, like the Foster, Greer, Thorbecke (FGT) class of poverty indexes.

This article uses a new numerical algorithm, which acts as optimal poverty group targeting. This method was first presented by Kanbur (1987), which focused on the theoretical rules of optimization. Then, based on the theoretical findings of Kanbur (1987), Ravallion and Chao (1989) have proposed numerical method that maximizes the reduction in the FGT (α=2)  index by group transfers, subject to a fixed budget. After that, Glewwe (1992) improved it theoretically, and finally, Araar and Luca (2019) proposed the method of optimal group targeting by modifying Glewwe (1992) method. In fact, the methodology of Glewwe (1992) is a generalization of Kanbor (1987) and Ravallion and Chua (1989) Method, but the mentioned methodologies focused on a subset of poverty indicators (e.g., squared poverty gap index) for which an analytical solution was possible. Contrarily, Araar and Luca (2019) proposed a new method, which is applicable to all additive poverty indices (such as the headcount or poverty gap rates and squared poverty gap indexes).This article uses income-expenditure data of rural households of Iran in 2020, and follows Araar and Luca (2019) methodology. In addition, to check the efficiency of this method, three indicators including the quality of targeting, inclusion and exclusion errors will be used.

In this article, economic and social characteristics of rural households in Iran were compared to targeted poverty alleviation programs. Based on the results, for the head count ratio, the targeting efficiency based on different household characteristics changes between 23.67 and 31.03 %, the population coverage rate changes between 38.93 and 100 %, and the sum of the inclusion and exclusion errors changes between 41.62 and 52.53%. Now, if the targeting is done based on the poverty gap index, the targeting efficiency will be between 42.18 and 48.02 %, the population coverage rate will be between 86.21 and 100 %, and the sum of the exclusion and inclusion errors will be between 46.96 and 52.53%. Finally, if the poverty severity index is used as the basis for targeting, the targeting efficiency will change between 53.99 and 59.51 %, the population coverage rate will change between 99.33 and 100 %, and the sum of the inclusion and exclusion errors will change between 48.92 and 52.53%. It is interesting to note that in targeting based on all three mentioned poverty indicators, the family size, number of members under 7 years old and the education of the household head are always the best characteristics for targeting poverty.

The main purpose of this article is to compare the different economic and social characteristics of rural households with the aim of identifying the best characteristics in order to targeting subsidies in Iran. According to the results of this article, the characteristic that should be taken into account in targeting is the family size, which the efficiency of targeting based on this characteristic is equal to 51.59% of targeting with complete information. The rate of exclusion and inclusion errors are zero and 52.53%, respectively. Finally, in the targeting based on the family size and squared poverty gap index, the population coverage rate is 100, which is very acceptable from the social point of view.  Paying attention to the changes in the poverty indices based on the household demographic characteristics is very important, because if the family size increases, the poverty indices grow strongly. As a result, the headcount, poverty gap and squared poverty gap indexes for families with six and more people become 2.5, 3.5 and 2.4 times the same index for households with 1-2 people, respectively.

International trade is usually associated with competition. During this competition, successful producers have lower production costs. Reducing the cost of production requires the use of different ways. One of these ways is the better use of primary production factors such as labor force. Thus, this paper attempts to investigate the effect of changes in foreign trade along with other effective factors on changes in labor force usage in Iran.

 
There are several methods to study the quality of labor force usage. The labor force productivity is considered as a criterion that is used in many researches. To this end, this study investigates the effects of foreign trade on labor force productivity changes in different production sectors. The data required for this research are provided from the input-output tables of 2011 and 2016, the national accounts and the results of the population and housing census for the years 2011 and 2016. For this purpose, first, symmetric tables of the sample years have been made with the assumption of sector technology, using consumption and supply tables of these years. Then, in order to calculate productivity and compare them in the sample years, the dimensions of the created tables have been standardized. Finally, using the Structural Decomposition Analysis (SDA) approach, the effects of changes in trade balance, along with export and import ratio to trade balance, export and import structure, self-sufficiency, production technology and employment on changes in labor force productivity are determined.
At the sectoral level, the value of the production of the industrial sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair and mining sectors, including crude oil and natural gas, has decreased due to reasons such as sanctions and low economic growth in these periods. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security /real estate and real estate services/transportation and agriculture sectors.

The total value of production in 2016 compared to 2011 has increased nearly 2006.70 million Rials at the price of 2016. The number of employed people in the country has increased by 2,113,120 people during this period. Because of these changes, the productivity of the country's labor force has reached from 1038.12 million Rials in 2011 (at the price of 2016) to 1029.84 million Rials in 2016, which shows a decrease of 8.28 million Rials.
At the sectoral level, the value of the production of the industry sector in 2016 compared to the corresponding value in 2011 (at the price of 2016) has decreased due to the recession prevailing in this sector. The value of products at fixed prices in trade and repair/ and mining sectors, including crude oil and natural gas, has decreased in these years due to reasons such as sanctions and low economic growth. In contrast, the value of production shows an increase at a fixed price in the public affairs, defense and social security/real estate and real estate services/, transportation/ and agricultural sectors.  In view of employment, the agricultural sector has faced a decrease in employment during the study period. In contrast, the industrial/, and trade and repair/ sectors have faced an increase in employment. Because of these changes, the industry/, trade and repair/ sectors have faced a decrease in labor productivity. Whereas the agriculture sector/, transportation/, public affairs administration, defense and social security/ and the activities of real estate and real estate service companies/ have faced an increase in labor productivity.
From the point of view of foreign trade, the industry sector has seen the largest increase in exports, while the electricity sector has faced the largest decrease in exports. In terms of imports, the industry sector has experienced the largest increase, while the education sector has experienced the largest decrease. The correlation coefficient between the exports of the sectors and the productivity of their labor force has been positive. While the correlation coefficient of the different sectors with the productivity of their labor force has been negative. However, the value of these correlation coefficients shows a decrease in 2016 compared to 2011.

The results of research show that foreign trade has improved labor productivity in the country. In addition, the exports of sectors have relatively similar relationship with the productivity of their labor force, in contrast, the import of goods has an inverse relationship with the productivity of their producing sectors. However, this issue has received less attention in 2016 compared to 2011, which has led to changes in the structure of exports and imports to reduce labor force productivity.