Economic Development
mahya allahgholi; Farshad Moameni
Abstract
Considering the economic complexity index as a development index due to its greater estimation power in predicting economic growth and income inequality compared to similar indices, along with shortcomings such as the inability to express the difference in the complexity levels of economies, it makes ...
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Considering the economic complexity index as a development index due to its greater estimation power in predicting economic growth and income inequality compared to similar indices, along with shortcomings such as the inability to express the difference in the complexity levels of economies, it makes the theoretical model to explain this index inevitable. In the social orders approach, the type of social order is mentioned as the difference between developed and developing economies, and in this article an attempt has been made to identified determinants of this index. In this study by descriptive analytical method the state of property rights, the business environment and the type of people`s access to organizations are known as three variables affecting this index. analyzing Iran`s economic complexity index during 10-period (2010-2020) and three indexes, international property rights, ease of doing business and economic freedom, respectively as an estimation of those variables, shows that the international property rights index has a stronger positive relationship with the economic complexity index than the other two indices.
Economic Development
mohaddaseh soleimani; Aliasghar Banouei; Esfandiar Jahangard; teymor mohamadi
Abstract
Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by ...
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Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by employing the fields of influence method. Technology changes are modeled as changes of one or more elements in the direct coefficients matrix and the impact of such changes in the Leontief matrix is measured. Here is the main question: Does the technology changes only impact a limited sector or the entire economical system? In other words, how would technology changes in one sector impact other sectors of economic system? The main goal in this paper is proposing a method which can measure how different sectors get impacted by changes at different levels such as one element, all elements, one row or one column and then evaluates the importance of different sectors. To this aim, Iran’s Input-Output tables over the period of 1365-1395 with the fixed price of Iran’s statistics center in 1390 is used. The impact of technology changes on each sector is measured using Leontief’s inverse matrix and the column field of influence approach (CFOI) approach. Our findings indicate that over this period of time, technological changes in the industry and then construction sectors have the most influence and the mining sector has the least influence on other sectors of Iran’s economy.
Economic Development
Amirhossein Pooreh; Abbas Hatami
Abstract
More than three decades have passed since the adoption of development policies in Iran following the Islamic Revolution. Despite these efforts, Iran remains in the fourth quarter of development and the first quarter of underdevelopment. While development and underdevelopment cannot solely be attributed ...
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More than three decades have passed since the adoption of development policies in Iran following the Islamic Revolution. Despite these efforts, Iran remains in the fourth quarter of development and the first quarter of underdevelopment. While development and underdevelopment cannot solely be attributed to policymaking, it is widely recognized as a critical factor influencing development. Employing the grounded theory approach, the present study sought to uncover the underlying reasons for the failure of development policy in Iran from the perspectives of experts and policymakers. First, semi-structured interviews were conducted with 22 experts and development policy managers. The collected data was analyzed through three stages of coding: open, axial, and selective. The analysis resulted in 629 primary concepts, which were refined and reduced into 78 subcategories, 24 main categories, and ultimately, one core category. The core category revealed that development policy in Iran suffers from a triangle of inefficiencies: the inefficiency of governance, the inefficiency of social structure, and the inefficiency of the elite order. These three inefficiencies are not isolated but interconnected, forming a kind of ominous triangle that undermines the efficiency of development policy in Iran. If these inefficiencies persist, Iran risks facing a double underdevelopment that can significantly hamper the pursuit of sustainable development. Introduction Development is one of the most pressing concerns for societies and nations worldwide. Various societies have pursued comprehensive and multidimensional progress by implementing diverse strategies, which are often structured as development policies. In the case of Iran, more than three decades have passed since the adoption of development policies following the Islamic Revolution. Yet, the country remains in the fourth quarter of development and the first quarter of underdevelopment, struggling to move beyond this phase. While development and underdevelopment cannot be attributed solely to policymaking, it is widely recognized as a critical factor influencing development. Relying on a grounded theory approach, this research sought to investigate the underlying reasons for the failure of development policy in Iran. It aimed to address the following questions: What are the causal conditions contributing to the inefficiency of development policy in Iran? What are the contextual conditions influencing the inefficiency of development policy in Iran? What are the intervening conditions affecting the inefficiency of development policy in Iran? What strategies can effectively improve the efficiency of development policy in Iran? What are the consequences of implementing strategies to improve the efficiency of development policy in Iran? Materials and Methods The current research used a grounded theory approach. The participants included experts, university professors, managers, and former administrators involved in development policy. A purposive sampling method with a homogeneous approach was applied to enrich the categories, dimensions, and components, as well as to achieve theoretical saturation. As a result, a total of 22 individuals were selected as participants. The data was collected through semi-structured interviews, and the interview process continued until theoretical saturation was reached. For data analysis, the three-stage coding method outlined by Strauss and Corbin (2015) was employed, encompassing open coding, axial coding, and selective coding. Results and Discussion The interviews were analyzed in three stages. During the open coding phase, 629 initial codes were extracted. At the next level of abstraction, these codes were organized into 78 subcategories, and finally categorized into 24 main categories. In the axial coding phase, the main and secondary categories were arranged according to paradigmatic dimensions, including causal conditions, contextual conditions, intervening conditions, strategies, and consequences. In the selective coding phase, a core category was identified, linking all the categories together. The causal conditions contributing to the inefficiency of development policy included: discourse conflicts, an anti-scenario futurism, a weak civil society coupled with a large mass society, the breakdown of elite communication, low institutional quality, an overly interventionist yet weak government, and the unrealistic, wishful thinking in program planning. The contextual conditions exacerbating development policy inefficiency were found to include poor timing, economic–political instability, and a lack of historical awareness. Intervening conditions identified were: epistemic foundations of anti-development, an absence of dialogue, an economic-focused and budget-oriented approach to planning, and an inappropriate composition of policy formulators.The strategies to enhance the efficiency of development policy in Iran, as identified by experts and policymakers, included: downsizing the government while empowering civil society, strengthening social capital, undertaking institutional and organizational reconstruction, adopting strategic foresight, achieving consensus among policymaking elites, and modernizing and screening development plans. If these strategies are implemented, Iran could experience multidimensional development, including improvements in life quality, social development, individual-cum-mental development, environmental livability, political development, and economic development. Conversely, failure to implement these strategies risks perpetuating multilayered underdevelopment, characterized by increasing unbalanced development, declining quality of life, reduced social satisfaction, rising costs, intensification of violence, and underdevelopment across economic, social, political, and environmental dimensions. Finally, the core category underlying these findings is the trinity of inefficiencies: incompetent governance, weak society, and elite disorder. Conclusion According to the research results, development policymaking in Iran suffers from a triangle of inefficiencies: the inefficiency of governance, the inefficiency of social structure, and the inefficiency of elite order. These inefficiencies are not isolated but are deeply interconnected, forming an ominous triangle that undermines development policymaking in Iran. If left unaddressed, it will entrench the country in a state of double underdevelopment and further delay the achievement of sustainable development.
Economic Development
Fariba Rashnoo; Ahmad Sarlak
Abstract
In an era of economic complexity, where goods and services are produced using advanced technologies and with significant diversity, achieving economic growth without environmental pollution has become one of the primary goals for nations worldwide. This objective necessitates measures such as investment ...
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In an era of economic complexity, where goods and services are produced using advanced technologies and with significant diversity, achieving economic growth without environmental pollution has become one of the primary goals for nations worldwide. This objective necessitates measures such as investment in knowledge-based production, which in turn relies heavily on investment in research and development. The present study aimed to examine the relationship between multidimensional economic complexity and inclusive green economic growth. Given the geographic proximity of some developed and developing countries, the research employed a spatial panel econometric method using data from these nations. The results indicated a significant relationship between inclusive green growth and economic complexity in both developed and developing countries. However, this relationship is relatively weaker in developing countries.IntroductionThe most crucial factor influencing the level of economic development in any country is the extent to which knowledge is generated and applied in its production processes (Kazemi, 2013). Moreover, the integration of knowledge into production significantly reduces greenhouse gas emissions (Barbieri, 2012). Economic complexity, through the knowledge channel, promotes resource efficiency, enhances the quality of production institutions, and facilitates the establishment of green productive structures (Hassan et al., 2022). Since developing countries often rely on the production of a limited range of goods, it is essential to examine their level of economic complexity. Furthermore, given the strong link between economic complexity and the technology required for renewable energy production, it is critical to examine the relationship between multidimensional economic complexity and economic growth through the technology production channel. In this context, countries like Iran must be analyzed in terms of economic complexity and compared with developed nations. Despite the importance of this issue, no study to date has explored the relationship between economic complexity and inclusive green economic growth across both developed and developing countries. The present research tried to address the following question: What is the relationship between economic complexity and green economic growth in developed and developing countries? To answer the question, the study first reviewed the theoretical foundations of green economic growth and economic complexity, followed by a discussion of the methods and models.Materials and MethodsThe present study relied on the model built upon the work of Mohammadi et al. (2023), who investigated the impact of economic complexity and renewable energy consumption on environmental pollution in developing countries. Spatial econometrics in Stata software was used to analyze the relationship between economic complexity and inclusive green economic growth from 2000 to 2022. This approach not only examines the relationship between independent and dependent variables but also incorporates the spatial characteristics of the locations involved, as highlighted in studies such as AbuGhunmi et al. (2023). Additionally, data from both developed and developing counties was used to conduct a comparative analysis. The first step in estimating the spatial panel model is to create the adjacency matrix. In this research, the proximity matrix for the seven OPEC member countries with common borders of spatial heterogeneity refers to the deviations in relationships between observations at different geographical locations. In this matrix, neighboring and non-neighboring countries are assigned a value of 1 and 0, respectively. Next, autocorrelation is tested through methods such as the Moran and Gray tests. Once autocorrelation is confirmed, the model type is determined through parent, multiple parent, and Akaike and Schwartz tests. Finally, the model is estimated.Results and DiscussionThe results of estimating the relationship between multidimensional economic complexity and green economic growth in developing countries are presented in Table 1, and those for developed countries are shown in Table 2.Table 1. Model Estimation Results With the Dependent Variable in Developing CountriesEffectsVariablesCoefficientProbabilityDirect effectsINF-0.080.000CO2-0.090.000R&D0.30.000TECHEX0.210.000EC0.120.000Indirect effectsINF-0.10.000CO20.110.000R&D0.240.000R&D(-1)0.210.000TECHEX0.200.000EC0.20.000Total effectsINF-0.110.000CO20.190.000R&D0.130.000TECHEX0.120.000EC0.210.000Spatial correlation coefficient-0.2360.039Hausman test7.110.81Source: Research findingsTable 2. Model Estimation Results With the Dependent Variable in Developed CountriesEffectsVariablesCoefficientProbabilityDirect effectsINF-0.060.000CO2-0.040.000R&D0.410.000TECHEX0.330.000EC0.240.000Indirect effectsINF-0.050.000CO2-0.060.000R&D0.360.000TECHEX0.210.000EC0.290.000Total effectsINF-0.030.000CO2-0.060.000R&D0.290.000TECHEX0.210.000EC0.390.000Spatial correlation coefficient-0.2490.029Hausman test6.990.78Source: Research findingsAs observed in the calculations, both the direct and indirect effects, as well as the total economic complexity, have a direct and significant impact on green economic growth. As expected, this effect is stronger in developed countries than in developing ones. The effect coefficient for total economic complexity in developing and developed countries is 0.21 and 0.39, respectively. These figures indicate that the overall impact of economic complexity on economic growth is greater in developed countries. This relationship can be explained using the Kuznets curve. According to the results, economic complexity fosters green economic growth by increasing the use of technology in production and reducing emissions.ConclusionThe results indicated that the impact of economic complexity on green growth is smaller in developing countries compared to developed countries. Additionally, since economic complexity reflects the use of advanced technologies and increased costs in the production process, the rise in technology use and in research and development expenditures will not only drive the production process towards greener, pollution-free methods but will also help reduce production costs over time. The coefficients presented in the table for both developed and developing countries showed the positive effect of economic complexity on green production and growth.
Economic Development
Sayed Amin Mansouri; Seyed Morteza Afghah; Behrouz Sadeghi Amroabadi; Hassan Farazmand; Yaghoub Andayesh; Ali Boudaghi
Abstract
One of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity ...
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One of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. The present research aimed to explore the role of the government and large local companies in income distribution. Khuzestan Province was chosen due to its unique characteristics in this regard. The study covered the period from 2006 to 2020, analyzing seasonal data using the generalized method of moments (GMM). The findings indicate that the government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. In contrast, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. The results suggest that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.IntroductionOne of the significant challenges in regional development is examining the role of local governments and their relationship with large local companies in income distribution. This challenge is particularly pertinent when large companies have national objectives, and most of their production capacity is capital-intensive and knowledge-intensive, but their operational area is locally focused on the user. Based on the available evidence, large companies in Khuzestan Province (e.g., oil, petrochemical, and steel companies), which are part of national entities, generate national income. However, the local population’s share of this income is small. Meanwhile, private companies in Khuzestan Province are under pressure to pay taxes. This has led to the perception among the people in the province that the presence of these national entities has resulted in a low local share of their income. In other words, the income generated by these companies flows out of the province, leaving the local population with a minimal share. In this respect, the present research aimed to explore the role of the government and large local companies in income distribution in Khuzestan Province during 2006–2020. Materials and MethodsThe primary research question is whether the government’s financial policies and the presence of large companies in Khuzestan Province significantly affect income distribution within the province. Using the generalized method of moments (GMM), the study relied on the seasonal data from 2006 to 2020 to address the research question. Results and DiscussionThe results indicate that government’s current and construction expenditures in the province have a negative and significant effect on the urban Gini coefficient. Conversely, the value-added variable of large industrial companies in the province has a positive and significant effect on the urban Gini coefficient. This suggests that the presence of large industrial companies has not only failed to reduce inequality but actually increased urban inequality in the province. The findings also show that both types of user investment and Berber knowledge are effective in reducing the urban Gini coefficient in Khuzestan Province. Additionally, the study found that air pollution in the province has a positive and significant effect on the urban Gini coefficient. This implies that increased pollution, caused by industrial activities, disproportionately impacts the lower classes as the benefits of these activities do not reach the lower-income population. Instead, these polluting industries impose negative external effects on the local population while contributing to increased inequality by introducing imbalances considering payments to national production factors. ConclusionAccording to the research results, the presence of large companies in the province has neither generated local benefits nor reduced income inequality in the urban sector. It is thus recommended that careful planning and coordination between large companies and provincial managers should be sought by adopting policies such as increasing local employment and training local workforce, thereby reducing dissatisfaction and income inequality in the province.AcknowledgementsWe express our gratitude to the Vice-Chancellor for Research Affairs of Shahid Chamran University of Ahvaz for his assistance in conducting this research.Conflict of interestThe authors declare no conflict of interest in publishing this articleFundingThis study is part of a research project related to industry between Shahid Chamran University of Ahvaz and the Management and Planning Organization of Khuzestan Province, financially supported by contract number 100z1310004 (971875).
Economic Development
Hossein Rajabpour; Farshad Momeni; Ali Nasiri Aghdam
Abstract
This article considers the effect of fiscal policy on inclusive development. Inclusive development is one of the concepts that has been introduced in the development economics literature in the last decade and especially with emphasis on the social and political aspects of development, the distribution ...
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This article considers the effect of fiscal policy on inclusive development. Inclusive development is one of the concepts that has been introduced in the development economics literature in the last decade and especially with emphasis on the social and political aspects of development, the distribution of development achievements among different sections of society is in focus. Since fiscal policies are one of the main instruments of the government to eliminate deprivation and imbalances, it is important to understand the effectiveness of these policies in this regard. In this study, the components of fiscal policy include the combination of expenditures and revenues and its effect on inclusive development in the period 1981-2018 in the form of two models of structural vector auto-regression has been studied. Findings show that most components of government fiscal policy except economic expenditures do not have a significant effect on the index of inclusive development and these economic expenditures have a negative impact on inclusive development. The results show that the government's fiscal policies have failed to achieve or accelerate inclusive development, and despite its legal mission, the government has not been successful in comprehensive expanding welfare and extending it to all social groups. Historical analysis also shows that since the beginning of the 2010s and with the intensification of sanctions and currency fluctuations, the relationship between fiscal policy and the index of inclusive development has been weakened. It seems that the reform of the budgeting process and the simultaneous attention to the two constraints of equality and sustainability in growth and development targeting for fiscal policy on inclusive development is essential.
Economic Development
Behrooz Shahmoradi; Mojgan Samandar Ali Eshtehardi
Abstract
Economic complexity is a concept that is used to express the ability of countries to produce complex products through the proper construction of technology structures in order to collect its diverse technologies and apply them. In this article, by using economic complexity approach, we aimed to identify ...
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Economic complexity is a concept that is used to express the ability of countries to produce complex products through the proper construction of technology structures in order to collect its diverse technologies and apply them. In this article, by using economic complexity approach, we aimed to identify the products in Iran’s technological capabilities frontier that leads the country to produce more diverse and complex products. For this purpose, by using four-digit SITC classification data, 86 products were identified. By producing and exporting them, the country can reach a higher accumulation of technological capabilities and thus a higher degree of diversification and economic complexity. Also, according to three criteria, the total number of competitors, the volume of world trade and the number of importing countries from selected products, 16 products in the world and 11 products in the region were picked up as the products in priority.