فهرست مطالب اسفندیار جهانگرد

Climate change is becoming a global crisis that can affect all aspects of human life on Earth, including the economy. So, protecting the environment and achieving sustainable development goals are now on the agenda of many governments. This article uses the Panel Smooth Transition Regression Model to test the role of information communication technology as a transition variable. In this research, it is investigated whether ICT can decouple the economic growth from the increase in pollution by changing the effect of productivity on CO2 emission. The goal is to show whether policymakers can use the development of the digital economy around the world to achieve better environmental and economic outcomes. This study was conducted on a global scale and data from 108 countries was used from 2003 to 2019. The results show that the co2 emission follows a PSTR model with ICT as a transition variable that changes the effect of total factor productivity on co2 emission in favor of the environment. ICT development will improve carbon efficiency and reduce climate change.

This article discusses the role of manufacturing in the economic growth of Iran using the logarithmic mean Divisia index (LMDI) method. The study identifies various drivers of industrialization and their impact on growth, including structural changes (productivity of labor and employment share in industrial factories) and employment scale. The LMDI method is used to analyze with a dataset from Iranian provinces between 1381 and 1399. The results show that industrialization has a positive and significant effect on economic growth, with structural changes having a greater impact than employment scale. The study highlights the importance of sustainable industrial development for economic growth in Iran.

The purpose of this paper is to find the ratio of the domestic price of natural gas to the export price that maximizes the welfare function of households. To achieve this goal, The administrative regulation of domestic gas prices is explicitly modelled in CGE Model. Regional gas markets can be characterised as being imperfectly competitive, so strategic behavior in a regional gas market modelled Cournot oligopoly structure. The database in this paper is the Social Accounting Matrix (SAM) of Iran 2013, which was prepared by the Majlis Research Center. The results show that the increase in the price of domestic natural gas under certain assumptions increases the level of economic efficiency and export demand function with a higher elasticity create a higher welfare level. Finally The optimal domestic gas price should be approximately 45% of the export price which is a lower ratio compared to the proposed ratio of 65% in the Law of the Fifth Development Plan of IRAN.

The structure of production networks determines the macroeconomic responses to sectorial shocks. Accordingly, key sectors are instrumental in transmitting supply and demand-side shocks. This article applies the methodology proposed by Savoie (2017) and network theory and implements the input-output tables of the Central Bank of Iran in 1988, 1993, 1999, 2004, 2010, and 2016 to examine the output multipliers of Iran's economic sectors. This article also compares the results based on Savoie's (2017) method with the driven results according to Friedkin's (1991) and Monize et al.'s (2008) methodology. The latter identifies key sectors using three centrality measures: total effect, immediate effect, and mediate effect. The results show that the "industry", "water, electricity, gas", and the "transportation and inventory" sectors have always had the highest connections with other sectors, and also have had the highest output multiplier. Besides, the "industry" and the "ICT" sectors are detected as the key and the developing sectors in Iran's economy, respectively. In addition, based on Friedkin's (1991) and Monize et al.'s (2008) methodology, the "construction" and "other services" sectors can foster Iran's economic growth; even though based on Savoie's (2017) methodology, these sectors relatively had a lower output multiplier.

In national accounts, costs related to intangible capital include computer databases, research and development, design, brand equity, company-specific training, and organizational efficiency as investments has expanded (Corrado, Hulten, and Sichel, 2005). When this broad view of investment is included in the analysis of the sources of growth, intangible investments account for one-fifth to one-third of labor productivity growth in the industrial sector of the United States and the European Union and East and South Asia (India, China and Japan ((Liang,2021 ؛Bhattacharya and Rath,2020 ؛ Rico and Cebrer-Bares,2020 ؛Hintzmann, Masllorens& Ramos Lobo,2021 ؛ Corrado, Haskel, Jona- Iommi ,2013؛Corrado, Hulten,and Sichel ,2009 ؛Marrano, Haskel, and Wallis ,2009 ؛Fukao, Miyagawa, Mukai, Shinoda, and Tonogi, 2009 ؛ van Ark, Hao, Corrado, and Hulten, 2009). In order to manage intangible resources as a source of growth at the macroeconomic level and a driver of value creation for individual firms, their measurement is very important(Corrado,Jonathan HaskelCecilia, Jona-LasinioMassimiliano Iommi,2012). It is obvious that many studies have focused on intangible investment, which shows the importance of this topic.Therefore, in this research, focusing on intangible investment, intangible investment has been measured. In Iran, due to the lack of statistics on how to calculate and estimate this type of investment, few studies have been conducted in the field of intangible investment measurement.   For example, in the study of Ostadzad and Hadian (2014) on the effect of research and development on economic growth and the study of Rahimi Rad, Heydari and Najarzadeh (2016) investigated the factors affectingthe intensity of research and development costs in industrial workshops of Iran. But so far, this study has not been done to measure all the components of intangible investment in Iran and investigate its effect on economic variables.In Iran, studies have been conducted to identify effective factors in determining the value of intangible assets in companies listed on the Tehran Stock Exchange. However, the measurement of intangible investment with comprehensive international definitions and separated by the four-digit ISIC code has not been done so far. As a result, in this research, it has been tried to use the approach of Corrado et al. (2005), which is a method that can be cited in most Valid studies of the countries of the world have been defined to measure intangible investment, and also according to the comprehensive definitions accepted at the international level of intangible investment, this importance has been implemented for Iran and this important economic variable has been estimated (Mashaikhi, Birami and Birami, 2013; Corrado et al, 2005; Fukao, Miyagawa, Mukai, Shinoda, and Tonogi, 2009).Therefore, in this study, the CHS approach (a comprehensive and accepted approach that has been used in most important studies) has been used to measure intangible investment(Corrado, Hulten, and Sichel,2005). One of the important activities in the functions of Iran's economy is the activities of factory industries approved by the Iranian Statistics Center. This article first aims to estimate the share and trend of intangible capital in these activities with the CHS approach, which due to the lack of studies in this field is very important for Iran's economy.Also, how it affects the productivity of the entire production factors is also one of the next topics of this study, which can be the way of economic approaches and important decisions in this field. In order to find answers to the research questions andapproach its hypotheses, the studied time period of 1996-2018 has been used for industrial workshops with ten workers and above, separated by the four-digit ISIC code. The model used is panel data with GMM method. The results indicate that intangible investment has a positive and significant effect on the productivity of all production factors. In the continuation of the research, the workforce has been divided into professional and non-professional workforce. The estimation of the economic model of this research shows that the effect of skilled labor on the total productivity of production factors in Iranian industries is about 6 times compared to unskilled labor.

This section presents a model that describes the relationship between intangible investment and factor productivity. Assume that the added value of the industry according to the four-digit ISIC code and ten workers and above in industry i and time t can be written as follows:   On the right side, L and K are labor and capital. Similarly, R is the flow of intangible capital services and A is a change term that allows for changes in productivity as L, K, and R become returns. We get the differential from equation (1):   So that εX represents the production elasticity of factor X, which is basically different according to input, industry and time. To empirically examine the role of intangibles as growth drivers, existing literature is used and it is done in two stages. First, consider the condition of ε. For a company with the lowest cost, we have: where s is the share of payments of this invoice in relation to added value. So this simply expresses the first-order condition of a firm in terms of production elasticities. If equation (1) is Cobb-Douglas, ε is constant over time, and equation (2) may be transformed into a regression model with constant coefficients. . If (1), for example, the elasticity of substitution is constant, then ε will vary over time at all levels, so (2) may be written as a regression model with interactions among all inputs. Now suppose that a firm can K, L or R variables can be used in other companies, industries or countries. Therefore, as Griliches pointed out, the industry elasticity ΔlnR in lnQ ∆ is a combination of input and output elasticity. As a result, we can follow Stiroh and we have (Griliches, 1992; Stiroh, 2002): which shows that the productive elasticities of the factors are equal to the weight of the factors. In addition, here there is the flexibility of deviation from the weight of the factors due to spillover. All this can be shown in equation Second, consider Δln Qi,t. As Grilichs and Shankerman pointed out, if we include the R&D inputs in conventional L and K and use a regression model to determine the R&D production elasticity, the results will be biased. The main point of this argument is that intangibles (such as research and development) are long-term assets and not intermediate inputs, and should be included as value-added investments (Griliches, 1980; Schankerma, 1981). Adding the normal as V (where the intangibles are treated as intermediates), we can write:  So that N is a real intangible investment and we have approximated the share of intangible investment costs in nominal Q as sR. Substituting (6) into (5), we have:  If we have the above expression in terms of ΔlnVi,t:  For simplicity we have assumed that Δ lnR = lnN∆ (as in the steady-state "max consumption" case). To model the efficiency of factors, the studies of Caves, Christensen and Diewert have been used, and the ∆lnTFP index is constructed with the translog production function as follows (Caves, Christensen, & Diewert, 1982):  where ∆lnTFPi,t= ∆lnTFPQi,t and ∆lnTFPQi,t is calculated as follows: Obviously, these approaches have advantages and disadvantages, but the estimation of this regression potentially reveals the factors that played a significant role in TFP and were suppressed.

To measure the intangible capital from Iranian factory data with four-digit ISIC code during 1996 to 2018 is 2190. The data shows that the ratio of intangible capital to production for all industries is equal to 68.41%, which shows the high impact of intangible capital on Iranian industries[1].The results show that, contrary to the traditional approach, intangible investment is not included in intermediate goods, but is included as an important factor in the production function. The high number of observations has helped to estimate the model more accurately. The employment impact factor, including professional and non-professional labor force, is approximately equal to 22/, which has a positive and significant effect on TFP.Also, if the physical capital grows by ten percent, the total factor productivity will grow significantly by 2.3 percent on average in the same direction. The remarkable thing about the impact of intangible investment is that if this type of investment grows by 10 percent amongvarious manufacturing industries, it can help to increase the TFP by 3.5 percent on average, which actually shows the role of intangible investments in factory industries in today's world.These results indicate that the production share of Iran's industries is not only focused on physical investment and labor, and there is another type of investment called intangible investment, which is not only effective but also in the extent of its effect on industrial production is superior to the rest of the components.By studying the world's major industries such as Microsoft, it can be found that its market value in 2006 is much larger compared to the value of its physical investment and labor force, and this difference in value is included in the area of intangible investment.Therefore, for most industries in different countries, it is not far from reality that the amount of intangible investment has a greater impact than the rest of the effective components. As a result, the hypothesis that there is a positive and significant relationship between intangible investment on the productivity of all production factors can be accepted at the level of 99% with an impact factor of /356.Also, for a ten percent increase in skilled labor, the TFP changes on average by approximately 0.6 percent, while this figure is approximately 0.1 percent for unskilled labor. These results show that in addition to intangible investment having a positive and significant effect on productivity, skilled labor also helps to grow the productivity of factory industries.

The importance of intangible investment is growing relative to the level of investment in the tangible assets we intend to invest with, including transport infrastructure, machinery and power plants, etc. As a result, the role of intangible investment becomes increasingly important for understanding and predicting productivity trends, economic growth and innovation. The importance of intangible investment, such as research and development or software, to describe productivity, competitiveness and economic growth, has long been recognized by economic literature and statisticians.Considering investment in intangibles leads to a better understanding of differences in productivity trends across countries. In this research, firstly, the measurement of intangible investment with the CHS approach for the four-digit ISIC codes of factory industries with ten employees and above was discussed. The high share of intangible investment compared to the total production of each industry shows the importance of this issue. Then the intangible investment variable was brought as the main component next to physical investment and labor in the production function. Observations showed that intangible investment had a positive and significant effect on the productivity of all production factors. Its high coefficient indicates the impact of intangible investment on TFP, and its omission in the production function caused TFP estimation to have a bias error. In order to show the impact of the professional workforce on the productivity of production factors, we separated the workforce into skilled and unskilled, and the results show that the impact of professional and expert workforce is almost six times greater on TFP.[1] The Statistics Center of Iran has been used to obtain the data. The years used are from 1996 to 2018. The estimated components are intangible investment, physical investment, labor force and production volume, to calculate the productivity index of production factors. The obtained data have been used separately according to the economic activity ranking classification code with version 4 from the Statistics Center of Iran. In the codes, we merged them with similar codes, and as a result, the number of codes is 132, which is the total number of data for the years 1996 to 2018 is equal to 2190, and the volume of data is worth considering for the correct estimation.

Economic growth acceleration is one of the critical topics and a relatively new concept in macroeconomic studies, which has received less attention in research related to economic growth in Iran. Examining growth acceleration aims to find turning points in the country's economic performance. Since growth spurts are related to limited changes in policy reforms, examining the acceleration of economic growth helps policymakers adopt a short-term growth strategy. With a review of global experiences, the acceleration of growth experienced in most of the developing countries has been exhausted and is not reproduced in their economy and does not continue. Therefore, evaluating periods of acceleration and reversal of economic growth is very important. In this study, after determining the period of accelerations and reversals of economic growth in Iran during the years 1955-2019, the period of growth acceleration is analyzed under the Within-Effect and Shift-Effect, using the Modified Shift-Share method. The research results show that the only period of accelerated economic growth experienced in Iran during the investigated period happened in 1965. Also, in 1975 and 1985, Iran's economy experienced a reversal in economic growth and entered a period of deep recession. Second, the Modified Shift-Share method results show that in 2014, both positive structural changes and within-sector productivity positively created growth acceleration, and the resulting growth was fast and stable.

The study of the relationship between the development of information and communication technology(ICT), financial development and economic growth has always been the focus of researchers and policy makers and due to differences in views on the relationship between those and the diversity of modeling of studies in this field, researchs has not resulted in a single result. On the other hand, with the development of technology and the introduction of fuzzy logic, developed modeling methods and the possibility of consolidating expert opinions in an intelligent inference system based on collective wisdom to create indicators of ICT development and financial development now exists. Accordingly, in this study, after consolidating the opinions of experts in a knowledge base consisting of 414 questionnaires on the relationship between the constructive sub-indicators of financial development and ICT development, fuzzy indicators of financial development and ICT development using the Mamdani Fuzzy Inference System(MFIS) then assess the short-term and long-term causal relationships between ICT development, financial development and economic growth in the form of a panel error correction model considering the Dynamic Common Correlated Effects(DCCE) using annual provincial data during The period from 2001 to 2017 was covered. After consolidating the opinions of experts and creating fuzzy indicators, only in the short run, the positive causal relationship from ICT development to economic growth was confirmed.

The question that is considered by researchers in the field of knowledge-based economy is that among the factors affecting intangible investment, does information and communication technology have a heavier weight than the rest of the factors? In this study, using the Corrado,Hulten and Sichel (CHS) approach, the measurement of intangible investment is calculated. In their research, intangible investment has been divided into three major parts: computer information, innovative assets, and economic competencies. Then these three components are divided into nine parts. In this article, we select the component of information and communication technology, which is the first component of intangible transitory capital, and its effect on Total Factor Productivity(TFP) has been investigated. The field of study is manufacturing industries with a four-digit economic activity classification code for employees of ten and above during the years 1996 to 2018. Using panel data and GMM, the productivity function was estimated for manufacturing industries. The results of this research show that ICT has a significant role on the productivity of all production factors, and its coefficient is higher than other intangible investment components.

The use of linear production functions in the structure of input-output model is one of the basic limitations of these models. Therefore, the present study, while eliminating the shortcomings of the standard supply-driven Gosh model by replacing the linear production function with the Cobb–Douglas production function in the supply-driven input-output model and introducing a nonlinear model, it compares the effects of rising gasoline prices on two standard linear models and a nonlinear supply-driven models. For this purpose, the input-output table of 2,016 of the Central Bank of the Islamic Republic of Iran has been employed to extract the non-linear supply-driven input-output model. Also, to calculate the value-added changes due to the increase in gasoline prices, gasoline subsidy figures in the hydrocarbon balance sheet in 2016 have been used. The results of this study show that in both models, due to the increase in gasoline prices, the production cost of all sectors increases, but the rate of increase in production costs in the standard supply-driven model is more than non-linear supply-driven model. The reason for this result is the possibility of substitution between inputs in the non-linear supply-driven model. In other words, in the non-linear Gosh supply-driven model, unlike the standard model, if the price of one of the inputs increases, other inputs at a lower cost will replace this input and the rate of increase in the cost of production of economic sectors will be less.

National input-output tables in Iran date back to the 1960s. However, Iran has been included in neither regional nor global international tables. Accordingly, the novelty of this article is adding Iran's national input-output table to the ICIO table. The 2016 national input-output table published by the Central Bank of Iran used for this purpose aligned with the proposed methodology of Diazenbacher et al. (2013) and Timer et al. (2015). The empirical findings of the countries' multiplier coefficients indicate that the lowest multiplier coefficient is related to Saudi Arabia (1.51). Iran's multiplier coefficient is about 1.75, indicating the weak link between Iran and the whole world economy. All in all, international sanctions, non-cooperation with international organizations and conventions, and inefficient economic policies are effective causes of few links of Iran with the global economy.

The main purpose of the article is to Identify of regions and activities that create greater potential value added tax for themselves and others. For this purpose, the column coefficient approach is used to calculate the input-output table of 9 regions including 24 activities for 2011. Findings indicate that although at the macro level, smaller regions create more potential value added tax capacity than larger ones, at the economic activity level, there is no direct relation between the share of value added of an activity and the potential VAT capacity of that activity. Based on the results, it is suggested that policy makers and regional planners pay special attention to the structure of the economy and the nature of the activities of that region. Also, the focus of regional development policies should be shifted to smaller areas that are more in line with space-based theories.

The COVID-19 pandemic became widespread in most countries of the world in late 2019. In addition to human casualties, it has also affected the economies of countries. According to IMF, the world economic growth in 2020 was -3.5 percent. However, the GDP’s growth rate of the Iran economy for 2020 has been positive and was reported as 1.5 percent, but there is evident that the economy has been affected by the coronavirus.  In this paper, we evaluate the effect of the COVID-19 pandemic on the production, employment, and value-added of the economy of Iran by using the hypothetical extraction method of Dietzenbacher & Lahr (2013) and the Input-Output general equilibrium model of Zaytseva (2000). We have used the data from the input-output table of the Iran Central Bank in 2016 and the employment figures of the Statistics Center of Iran. The results show that the production and the value-added of the economy will decrease by 4.3 and 4 percent respectively. Among the value-added components, mixed-income and net operating surplus experienced the highest declining growth rate. Also, about 6.5 percent of the country's employees have been affected directly and indirectly by the Coronavirus.

Health Inequality Can be defined as Differences Variations and Disparities in Achieving Health across a Group of People. These Disparities have become a Major and Main Public Health Concern and Most Countries Seek to reduce this Desperation by Putting in Place Policies. Policies and Interventions Which Directly Address the Social and Economic Factor that Drive Health Inequalities are Likely to be Most Effective in Reducing Health Inequality. It is Here That Identifying the Factors affecting this Inequality Becomes Important. The Study Aimed to Determine Factors Associated with Health Inequality. For Achieving the Purpose, Panel Data Regression Technique for 31 Iran Provinces from 2009_2018 was used. The Health Inequality Index Was Measured Using Gini Coefficient. The Results of This Study Show that the Coefficient of Health Inflation, Income Inequality, Education and Unemployment is Positive and Is Statistically Significant. Also, Income, Insurance, and Government Construction Budget Helps Reduce the Health Inequality in Regression.

Taxes, especially complications, are the main source of funding for public revenue and one of the most effective tools for government fiscal policy. Reforming the structure of Tax laws as the most essential part of Tax policies has a substantial place in the set of government fiscal policies. Considering that VAT policy as one of the methods of reforming the country's Tax structure instead of Tax of the services' and goods' collection in 2008 year and the importance of altering in the country's Tax policies in this study using the indicators of Tax revenue share in covering government expenditures, the ratio of Tax revenues in GDP and the share of Tax revenues in total public revenues to compare the efficiency of this We have addressed two Tax policies with a fuzzy approach. The research findings show that the efficiency of toll collection policy during the years 2001 until 2008, the highest value is 0.531 in 2003 and in 2008 the lowest efficiency is 0.495. The efficiency of the value-added system with an average of 0.52525 was higher than the toll collection system with an average of 0.5135 and an upward trend. As a result, it can be concluded from the research findings that the value-added Tax policy is more effective than the Tax policy called Tax of the services' and goods' collection.

The present paper aims to identify the most important factor that explains productivity changes in energy use in Iran over the period of 1385-1394-. Towards this end, the authors have utilized three symmetric industry by industry input-output tables namely, IOT at 1385 constant prices introduced by research center affiliated to Iranian parliament, IOT at 1390 constant prices introduced by Iran’s statistics center and the 1394 -IOT updated by RAS method. Jacob (2003) attribute productivity Changes in energy use to six factors.  The authors have applied the Jacob formula to decompose productivity changes into six cause factors namely, changes in value added, changes in energy consumption, changes in domestic energy supply, structural changes -technology factor, final demand changes, inter industry final demand changes pertaining to agricultural, industry, power, transportation and other service sectors. The results of this study reveal that productivity changes in energy use is negatively affected by value added changes while changes in energy consumption in agriculture and power sectors had a declining impact on productivity and the effect of other factors in productivity changes has been negligible over the period under study.

ICT plays an important role in accelerating economic growth, especially in today's age of the Internet and mobile telecommunications. Due to the upward trend in the use of information and communication technology in the countries of the world, this part of the economy demands a lot of attention. Improved policies due to the impact of information and communication technology on the economy are one of the top programs of governments in developed and developing countries.A review of the literature shows that few systematic studies have examined the role of information and communication technology in GDP growth and the impact of various variables on the role of information and communication technology has not been sufficiently studied.The present study uses systematic approach and system dynamics methodology and examine interactions of ICT variables including ICT access, ICT development, ICT usage etc. with macroeconomic variables such as GDP, total factor productivity, ICT Capital examines ICT's value-added share of GDP and so on and presents a conceptual model of the role of ICT in GDP growth. The qualitative model designed in this study can be the basis for future quantitative research and mathematical simulation with a systematic approach to information and communication technology and GDP.

Considering the various variables affecting the relationship between information andcommunication technology and GDP growth and the interaction and non-linear effects ofthese variables on each other, it is necessary to provide a model to predict the favorable orunfavorable effects of ICT policies on GDP using simulation. The present study examinesthe interrelationships of information and communication technology variables andmacroeconomic variables with a systemic approach and using system dynamicsmethodology. After examining the reference modes of the variables, the cause and effectmodel is designed and the feedback and then the rate and stock variables are identified andthe stock-flow model is created. The results of model implementation have been able tocover reference modes well. The model designed in this research can be used for macrodecisions and policy making in the field of information technology.

In recent years the business model has been attracted researchers' and practitioners' attention due to its impact on the success of every business. A collection of research in the field of art shows little attention to the selection and design of the art business model, and this issue can be considered as one of the reasons for not doing the right thing in the business of this area. This subject has been grounded to investigate business models to identify suitable methods for Iranian handicraft activities in the present study. Using mixed-method, after reviewing the literature related to the topic, the theoretical framework was identified. Then, in the quantitative section, using the Correlation method, we studied a set of methods used in the Laljin pottery business based on the Osterwalder model. We found that the Osterwalder model, does not cover handicraft business in several elements and there is a need for a different business model. In the qualitative section using grounded theory, based on the effectuation theory, we propose a new efficient business model, called "Fish Business Model". In this model, entrepreneurs are like fishes moving in the wavy sea, and using their real capabilities they build their business model. This model presents suitable managerial and executive methods of a business of production and supplying handicraft products as a coherent process and covers all international rules and regulations.

The purpose of this paper is decomposing total factor productivity growth with reconciling both of the input- output and linear programming models in general equilibrium framework rely on the shadow prices of production factors as their real values in an open economy and studying its performance in Iran. For this purpose, input- output tables of central bank of Iran aggregated in 7 sectors are used for years 1367 and 1378. In this research, we decomposed total factor productivity growth to three factors named technical changes, terms of trade effects and efficiency changes which are reached by solving a linear program of maximization of domestic final demand using the framework of Raa and Mohnen (2002) paper. In this regard, the main question is that which of the three factors listed above is the major factor of total factor productivity growth in Iran? Based on the results, technical changes with share of 91 percent were the major factor of total factor productivity growth in Iran in our study period. 

The Double dividend hypothesis briefly demonstrates that by replacing different kinds of distortionary taxes with environmental ones, not only the lesser pollutants would be emitted (the first merit), but the more productivity and public welfare would be gained (the second one). Given the urgent need of reducing emissions in Iran, levying taxes on carbon, aimed at reducing carbon dioxide by 12 percent, is simulated at present article by a computable general equilibrium model which hypothesized three recycling tax incomes scenarios. In order to calibrate the model, the social accounting matrix of 1390 is used, which comprises of 26 sectors, 36 commodities and two type of households, based on the input-output tables of the Iranian Statistics Center. The results of the present research show that the goal of 12 percent reduction of the emission would be met by 51.3 Rials taxing per each kg carbon dioxide in the scenario of restoring the whole taxes to the households, 73.5 Rials in the scenario of reducing production taxes and finally 58 Rials in the scenario of reducing labor taxes. In all the three scenarios, increase of the real consumption budget of household and the equivalent welfare index is evident. In the first scenario, employment decreases and in the second and third ones, it increases, whereas the real GDP decreases and in the second and third ones, it stands approximately the same. The results of the present research bear out the weak form of the double dividend hypothesis, in the sense that the welfare effects of reducing distortionary taxes are more than those of restoring the whole distortionary ones. The strong form of the hypothesis, however, is not approved in Iranian economy. Moreover, the reduction of labor tax policy, is accompanied by the optimum welfare and viability effects.