Anahita Roozitalab; Esmaiel Abounoori
Abstract
Education, as one of the key indicators of human development, plays a decisive role in reducing social and economic inequalities. Unequal education exacerbates income disparities, while economic inequality restricts balanced access to education. This study examines the impact of different educational ...
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Education, as one of the key indicators of human development, plays a decisive role in reducing social and economic inequalities. Unequal education exacerbates income disparities, while economic inequality restricts balanced access to education. This study examines the impact of different educational levels on income distribution inequality in Iran using Household Income and Expenditure Survey (HIES) data from 1984–2023. In this research, the Gini coefficient was calculated for each educational level. The effect of educational inequality (measured by the standard deviation of educational expenditures) on income inequality was then analyzed using the Panel ARDL econometric model, with average household expenditures and unemployment rates as control variables. The results indicated that educational inequality in Iran followed an increasing trend over time, reaching its highest level in recent years. Furthermore, the findings revealed that both educational inequality and unemployment rates had a positive and statistically significant effect on income inequality. Additionally, the results demonstrated that average household expenditures within each educational group had a negative and significant impact on reducing income inequality. Finally, based on the study’s findings, it is recommended that the government implement appropriate policies to reduce educational inequality and enhance access to higher education for all members of society, particularly low-income groups.
Introduction
Income inequality, as a fundamental challenge for developing economies, has consistently garnered the attention of policymakers and researchers. Among the contributing factors, the role of human capital, and specifically the level of education, stands out as a crucial determinant of income distribution (Schultz, 1961; Becker, 1964). Human capital theories posit that increased educational attainment leads to the enhancement of individuals' skills and productivity, consequently providing access to higher-paying job opportunities (Mincer, 1974). Conversely, unequal access to educational opportunities at various levels can exacerbate income inequality within society (Bourdieu, 1986).
In the Iranian economy, despite efforts to expand education, significant disparities in income distribution persist. Examining the relationship between educational attainment and income distribution in this country, considering its unique economic and institutional structure, is of paramount importance. This study focuses on different educational levels to investigate the factors influencing educational inequality in Iran during the years 1984–2023. It seeks to answer the fundamental question of whether and how different levels of education impact income distribution in the country. Analyzing this relationship can lead to a deeper understanding of the factors driving income inequality and provide a basis for designing more effective educational and economic policies aimed at reducing this disparity.
Methods and Materials
To examine the impact of education on income inequality in Iran during the period 1984–2023, this research utilizes data from the Household Income and Expenditure Survey conducted by the Statistical Center of Iran. The methodology comprises two main parts: First, the calculation of the Gini coefficient for each educational level (elementary, middle school, high school, associate's degree, bachelor's degree, master's degree, and doctorate). This was achieved by extracting household expenditure information from the questionnaires and calculating the cumulative relative frequency of households and their expenditures at each educational level.
Second, the investigation of the relationship between education and income distribution within the framework of income functions based on human capital theory. This theory posits that investment in education leads to an increase in individuals' income and affects the income distribution of society. The research employed a simple income function and its generalization for N years of schooling to examine how the distribution of the rate of return on educational investment, the intensity of investment, and years of schooling impact relative income distribution. Finally, a model for analyzing income distribution at different educational levels in Iran was estimated, where the Gini coefficient of each educational group was considered a function of the dispersion of educational expenditures, the average household expenditure, and the unemployment rate at the same educational level.
Results and Discussion
The results of the panel ARDL (Autoregressive Distributed Lag) econometric model indicate that an increase in the average household expenditure leads to a reduction in income inequality (Gini coefficient) in the studied educational levels in both the short and long run, with the long-term effect being stronger. This finding contradicts the Kuznets curve hypothesis, suggesting that in this dataset, increased expenditures directly improve income distribution. In contrast, the dispersion of educational expenditures has a positive and significant impact on the Gini coefficient, implying that greater inequality in educational expenditures exacerbates income inequality. The unemployment rate also has a positive (although statistically insignificant at the 5% level) effect on the Gini coefficient in both the short and long run, such that an increase in unemployment leads to higher income inequality, with a larger long-term effect. The error correction coefficient indicates that approximately 44% of the short-run disequilibrium in the Gini coefficient is adjusted within approximately two periods, suggesting a moderate speed of adjustment towards the long-run equilibrium.
Conclusion
This research, by examining the impact of different educational levels on income inequality in Iran during the years 1984–2023, revealed that income inequality among graduates of higher education levels is significantly greater, which contradicts the expectation of decreasing inequality with increased education. An increase in the average household expenditure was associated with a decrease in inequality, while the dispersion of educational expenditures and the unemployment rate were linked to an increase in inequality. The results of the ARDL model suggest that the impact of independent variables on income inequality occurs with a time lag. It is recommended that to reduce inequality, educational infrastructure in deprived areas should be developed, financial aid should be provided to low-income students, educational programs should be aligned with labor market needs, and job opportunities should be created for graduates. Attention to multidimensional inequality indicators is also necessary for a more accurate understanding of the situation.
Behnaz Gorgich Moghaddam; Marziyeh Esfandiari; Reza Ashraf Ganjoei
Abstract
In recent years, the Iranian economy has been subject to severe fluctuations in macroeconomic indicators such as inflation rate, exchange rate, and economic growth. These fluctuations not only complicate economic policy decisions but can also affect household consumption. Since consumption is one ...
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In recent years, the Iranian economy has been subject to severe fluctuations in macroeconomic indicators such as inflation rate, exchange rate, and economic growth. These fluctuations not only complicate economic policy decisions but can also affect household consumption. Since consumption is one of the main components of aggregate demand and a driver of economic growth, we aim to understand how households respond to economic uncertainties. By investigating uncertainty in macroeconomic changes, the present study attempts to fill the gap in Iranian economic literature and provide a more accurate insight into economic decision-making for designing supportive policies in conditions of economic instability. This study aims to investigate the effect of macroeconomic uncertainties, including inflation rate and unemployment rate, on household consumption in Iranian provinces. In macroeconomic theories and consumption theories, economic uncertainty can cause consumers to reduce their consumption in the market, particularly of luxury purchases, because individuals can save their financial resources to deal with future risks. The research method is descriptive-analytical and panel data related to the provinces of Iran were used in the period 1395 to 1401. Econometric modeling was carried out using a dynamic model based on the generalized method of moments (GMM). For this purpose, macro uncertainties including inflation and unemployment were first extracted by using the GARCH model. The research findings show that inflation rate uncertainty does not have a significant impact on household consumption. However, global economic policy uncertainty and unemployment rate uncertainty have an impact on household consumption patterns.IntroductionConsumption is one of the most important economic factors in policymaking and is considered an influential factor in the lives ofhouseholds (Alp & Seven, 2019). According to the existing literature, household consumption is affected by several influences. However, it seems that one of the main factors affecting household consumption is their uncertainty about the future state of the economy. When economic agents find it difficult to make decisions about the possible path of the secure economy, this forces individuals to change their decisions (Kimball, 1990, Eberly, 1994). Macroeconomic uncertainty is expected to have a negative impact on household consumption and consequently affect the health of society and economic growth.This study examines the effect of uncertainty on household consumption, and it is the first study to simultaneously examine the effects of uncertainty, the unemployment rate, and several specifications of household consumption in the provinces of Iran.Methods and MaterialThe research method was descriptive-analytical and panel data related to the provinces of Iran were used in the period 1395 to 1401. Econometric modeling was carried out using a dynamic model based on the generalized method of moments (GMM). For this purpose, first the uncertainty of macro variables, including inflation and unemployment, was extracted using the GARCH model. The data used in the present study are extracted from the website of the Statistical Center of Iran and the World Bank. To answer the questions of the present study, the model was adapted from the study of Nam et al. (2021) as follows:yit= c0 + b1 WEUit + bi (control variables) + eit The model components include the following:yit is the growth of annual consumption for each household, WEUit represents the uncertainty index that is used in the present study to estimate the global economic policy uncertainty index. This index is also obtained through the GARCH family for each province in each year for the unemployment rate and the inflation rate. After running separate regressions using an uncertainty index in a time index, we compare the economic and statistical significance of b for each index. Control variables include household income, income tax, urbanization rate, proportion of population under 15 years of age, proportion of higher education, and government spending.Results and DiscussionIn this study, different types of uncertainty have been used to estimate the impact of uncertainty on household consumption. These uncertainties include global uncertainty, trade uncertainty, inflation uncertainty, household income uncertainty, unemployment rate uncertainty, and government spending uncertainty. These explanatory variables were selected to estimate the impact of uncertainty on household consumption behavior. These uncertainties have been obtained through estimation using the GARCH family model. According to the research of Kolshin (2022), inflation expectations have a great impact on the consumption of food goods and make prices sensitive to monetary policy, but in the present study, according to the results obtained, inflation uncertainty has no effect on the consumption of food and non-food consumption. According to the research of Bean et al. (2024), increased unemployment has caused a decrease in calorie consumption in households. It has also been concluded that this unemployment uncertainty has affected low-income households more and they have been more vulnerable. In the present study, it was found that unemployment uncertainty has significantly increased the consumption of food and non-food goods. According to the studies of Su et al. (2023), uncertainty in economic policy has caused instability in the exchange rate, and this instability leads to an increase in the price of imported foods and a decrease in access to food. However, according to the current study, economic policy uncertainty, or global uncertainty, has had the greatest impact on the consumption of goods, and in many cases has caused people to face high risks.ConclusionAccording to the study findings, in general, the impact of global uncertainty is greater than domestic uncertainty. Global economic policy uncertainty and unemployment rate uncertainty have a negative impact on household non-food consumption. While global uncertainty reduces food and non-food consumption, unemployment rate uncertainty increases food consumption and reduces non-food consumption. Inflation rate uncertainty does not have a significant impact on food and non-food consumption. However, inflation reduces household consumption expenditure on food and non-food items, and the impact on food is greater. Therefore, inflation rate fluctuations in Iran do not have a significant impact on food and non-food consumption. The reason can be considered the continuous existence of the inflation rate in Iran. The study by Shafiee et al. (2017) concluded a negative relationship between household consumption expenditures and uncertainty, but the study did not separate food and non-food expenditures and did not examine them at the provincial level.
Nadia Mirzababazadeh; Somayeh Shahhosseini; ُSamaneh Norani Azad
Abstract
Export diversification remains a pivotal theme in international trade literature. Statistical evidence indicates that the export baskets of developing economies are predominantly composed of traditional commodities. Consequently, these nations strive to diversify their export portfolios by incorporating ...
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Export diversification remains a pivotal theme in international trade literature. Statistical evidence indicates that the export baskets of developing economies are predominantly composed of traditional commodities. Consequently, these nations strive to diversify their export portfolios by incorporating a broader range of manufactured goods. This imperative is particularly acute for oil-exporting developing countries, where diversification is essential to mitigate the economic risks associated with high export concentration in the hydrocarbon sector.
Producing a diversified range of goods is often technology-intensive—a capability that firms in many developing nations frequently lack. Access to a wider variety of imported intermediate and capital inputs—characterized by competitive pricing and superior quality—can play a crucial role in bolstering export competitiveness. These imports facilitate productivity enhancements, reduce production costs, and improve product quality. Given the significance of this issue, elucidating the role of technology spillovers embodied in imported intermediate and capital goods and examining their impact on export diversification are vital for formulating effective industrial development strategies.
This study aims to determine whether the importation of intermediate and capital goods exerts a positive and significant impact on Iran's export diversification. To this end, the research employs a panel data model using data from Iranian manufacturing industries at the two-digit ISIC level for the period 2006–2021 (1385–1400 SH). Furthermore, the study conducts a granular analysis of how these imported inputs affect export diversification across specific industrial sub-sectors.
Method and Material
This study investigates the determinants of industrial export diversification in Iran from 2006 to 2021, with a specific focus on imported intermediate and capital goods. The analysis utilizes a panel data model based on Iranian industries classified at the two-digit level of the International Standard Industrial Classification (ISIC), Revision 4.
To quantify the impact of imported inputs on industrial export diversification ( ), the following econometric specification is estimated:
In Equation (1):
denotes export diversification;
is the real effective exchange rate (defined as );
and represent imports of intermediate and capital goods, respectively;
denotes research and development expenditures;
indicates the degree of economic openness; and
represents the Gross Domestic Product per capita.
The export diversification index for two-digit industries is calculated using the Theil index, as shown in Equation (2):
Here, represents the exports of the industry with the -th four-digit code in period . Consequently, denotes the total exports of the two-digit industry.
The real exchange rate ( ) is calculated using Equation (3). The data comprises the official exchange rate, the Producer Price Index (PPI) disaggregated by Iranian industries, and the value-added deflator of U.S. industries (as a proxy for foreign prices), with 2015 as the base year.
Data for imported intermediate goods is derived from the value of foreign raw materials, packaging supplies, and non-durable tools. Data for imported capital goods is obtained from the purchase or acquisition of foreign capital assets. The Research and Development (R&D) variable is sourced from statistics on research and laboratory expenditures, disaggregated by industry. These data were extracted from the Statistical Center of Iran's database on industrial establishments with 10 or more employees across 23 distinct industries. GDP per capita was retrieved from the World Bank. All nominal variables were deflated using the industry-specific Producer Price Index (PPI) with a base year of 2015.
The degree of economic openness is calculated as per Equation (4):
Consistent with theoretical foundations, it is expected that all variables, except the real exchange rate, will have a positive impact on Iran's industrial export diversification.
Results
The empirical estimation results, reported in Table 3, indicate that imported intermediate and capital goods have a positive and statistically significant impact on Iran's industrial export diversification. Specifically, a 1% increase in the imports of capital and intermediate goods is associated with increases in export diversification of 0.01% and 0.036%, respectively. Furthermore, GDP per capita and economic openness exert a positive and significant influence on diversification. Conversely, the real exchange rate and R&D expenditures exhibit a negative impact on industrial export diversification.
For a more comprehensive analysis, the impact of imported inputs was examined at a disaggregated level across two-digit industry codes. The results in Table 4 reveal significant heterogeneity across sub-sectors. Notably, the elasticity of export diversification with respect to capital goods imports is highest in the Manufacture of food products industry (coefficient = 0.02). Similarly, the impact of intermediate goods imports peaks in the Manufacture of beverages industry (coefficient = 0.15). However, in the Manufacture of tobacco products and the Manufacture of pharmaceuticals, medicinal chemical, and botanical products, the effect of these imported inputs on export diversification is statistically insignificant.
Conclusion
This study examined the influence of imported intermediate and capital goods, along with other factors, on industrial export diversification in Iran from 2006 to 2021. The analysis utilized a panel data model employing data from Iranian industries at the two-digit ISIC level.
The empirical findings demonstrate that imports of both intermediate and capital goods exert a positive and statistically significant impact on the export diversification of Iran's manufacturing industries. Furthermore, disaggregated analysis indicates that the magnitude of this effect varies across different industrial sub-sectors. Consequently, trade strategies should prioritize facilitating the importation of intermediate and capital goods.
Moreover, support policies regarding these inputs should be designed in a targeted, sector-specific manner to maximize industrial development.
Tahereh Ashtiani; Akbar Pourfaraj; Esmail Ghaderi; Zohre Dehdashtishahrokh
Abstract
Introduction
Export performance has long been recognized as a critical indicator of firms’ competitiveness and a key driver of economic growth, particularly in developing and resource-dependent economies. In the context of increasing globalization, intensifying international competition, ...
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Introduction
Export performance has long been recognized as a critical indicator of firms’ competitiveness and a key driver of economic growth, particularly in developing and resource-dependent economies. In the context of increasing globalization, intensifying international competition, and heightened environmental uncertainty, understanding the determinants of export performance has become an essential concern for scholars, managers, and policymakers. For countries such as Iran, where reducing dependence on oil revenues and expanding non-oil exports are strategic priorities, identifying the most influential drivers of export performance is of particular importance.
Literature Review
Despite the extensive body of literature on export performance, prior empirical studies have produced mixed and sometimes contradictory findings regarding the magnitude and significance of its determinants. These inconsistencies can largely be attributed to differences in research contexts, methodological approaches, sample sizes, and measurement indicators. Moreover, most existing studies examine export performance determinants in isolation, without providing an integrated and cumulative assessment of their relative importance. The absence of comprehensive meta-analytic evidence in the Iranian context has further limited the generalizability and robustness of prior conclusions. Addressing these gaps, the present study aims to systematically synthesize existing empirical evidence and quantify the effects of key determinants of export performance in Iran through a meta-analysis approach.
The primary objective of this research is to identify, compare, and prioritize six major factors influencing export performance, namely environmental factors, competitive advantage, export strategies, market orientation, innovation, and export commitment. These variables have been repeatedly emphasized in both domestic and international literature as central drivers of export success, yet their relative contributions remain unclear. By integrating findings from multiple empirical studies, this research seeks to provide a more reliable and generalizable estimation of effect sizes and to offer a comprehensive conceptual understanding of export performance in the Iranian context.
Methods and Materials
This study adopts a quantitative meta-analysis approach, which is particularly suitable for addressing contradictory findings across empirical studies, as it combines effect sizes from independent samples to produce statistically more powerful and precise estimates. The statistical population of the study consists of empirical research examining export performance and its determinants in Iran. A systematic search was conducted across major domestic and international databases, including Google Scholar, SID, Magiran, Irandoc, Noormags, ScienceDirect, Emerald, Springer, Wiley, and Scopus. Studies published between 2000–2024 (international sources) and 1380–1403 SH (Iranian sources) were considered.
Following a rigorous screening and selection process based on predefined inclusion criteria—such as relevance to the research hypotheses, availability of sample size and test statistics, and acceptable levels of validity and reliability—40 empirical studies were selected for inclusion in the meta-analysis. The selected studies encompass a wide range of industries and predominantly employed structural equation modeling and regression analysis. Effect sizes were calculated and analyzed using Comprehensive Meta-Analysis (CMA2) software. To ensure robustness, both fixed-effect and random-effect models were considered, and heterogeneity among studies was systematically assessed.
Results
The meta-analysis of 40 selected studies reveals that all six identified determinants exert a statistically significant and positive influence on export performance within the Iranian context. Among these, Market Orientation (ES = 0.765) and Innovation (ES = 0.576) emerge as the most powerful drivers, indicating that firms with robust customer intelligence and R&D capabilities are significantly better positioned to penetrate foreign markets. Environmental Factors (ES = 0.556) also show a high impact, reflecting the extreme sensitivity of export activities to macro-level uncertainties such as sanctions and exchange rate volatility. Furthermore, the results confirm the importance of Marketing Strategies (ES = 0.422) in terms of pricing and distribution, as well as Competitive Advantage (ES = 0.397) and Export Commitment (ES = 0.310). While all variables are significant, the disparity in their effect sizes suggests that internal proactive capabilities (market-driven and innovative approaches) are more decisive than purely structural or commitment-based factors in sustaining international presence.
Conclusion
The meta-analysis of 40 studies underscores that environmental factors, competitive advantage, export strategies, market orientation, innovation, and export commitment are pivotal determinants of international success. The findings reveal that achieving superior export performance requires a strategic alignment between internal firm capabilities and environmental volatility. Crucially, the qualitative assessment indicates that in contexts characterized by economic instability, such as Iran, macro-shocks (e.g., exchange rate fluctuations and political risks) act as significant moderators that can diminish the positive impact of firm-level variables like market orientation. Therefore, sustainable export growth necessitates a dual approach: enhancing managerial resilience and innovation at the micro-level, supported by macroeconomic stability and proactive international diplomacy at the macro-level.
Esfandiar Jahangard; Alireza Jahangard
Abstract
This study investigates the decomposition of value-added in Iran’s gross exports with a focus on its trade relations with key global economic groups, particularly BRICS and Shanghai Cooperation Organization (SCO) member countries. To achieve this, four major decomposition methods are applied, ...
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This study investigates the decomposition of value-added in Iran’s gross exports with a focus on its trade relations with key global economic groups, particularly BRICS and Shanghai Cooperation Organization (SCO) member countries. To achieve this, four major decomposition methods are applied, namely those proposed by Koopman et al. (2014), Wang et al. (2013), Miroudot and Ye (2021), and Borin and Mancini (2023). The study emphasizes the Borin and Mancini (2023) framework, which is source-based and exporter-oriented. By incorporating Iran into the 2016 Inter-Country Input-Output (ICIO) database through national input-output data, this paper offers an empirical analysis of Iran’s integration in global value chains (GVCs). The results highlight that Iran’s participation in GVCs is extremely limited, both in upstream and downstream linkages.IntroductionSince the 1990s, global trade has increasingly been structured around global value chains, where intermediate and final goods cross borders multiple times. Traditional trade statistics are insufficient in capturing the true economic contributions of each country within these chains due to double counting. This issue is particularly relevant for Iran, where understanding the sources and destinations of value-added is crucial for policy design. By leveraging inter-country input-output (ICIO) data, this study examines Iran’s export value-added structure and its relation to major global economic blocs.MethodologyThe paper utilizes the 2016 ICIO table, augmented to include Iran, which provides a detailed 42×42 sector-country matrix. Value-added decomposition is conducted using four distinct frameworks, differentiating between domestic value-added (DVA), foreign value-added (FVA), returned value-added (RVA), and double-counted components (DDC and FDC). Emphasis is placed on Borin and Mancini’s (2023) source-based decomposition, using the Exvatools package and bilateral trade flow analysis.Results and DiscussionIran’s total gross exports in 2016 amounted to $97.3 billion, of which 88.9% was domestic value-added and 11.1% was foreign value-added. The VAX (exported and absorbed domestic value-added) component accounted for 88.6% of exports, while the returned value-added (RVA) was just 0.2%. In comparison with BRICS and SCO countries, Iran’s foreign value-added content was significantly lower, suggesting weak upstream integration. Similarly, the double-counted content (DDC and FDC) was minimal, indicating limited engagement in multistage international production processes. Iran’s major trading partners absorb the majority of its exported value-added, while very little is returned or cycled through multiple stages. Furthermore, import-side decomposition showed that most of Iran’s imports are final goods rather than intermediate inputs.ConclusionThe findings confirm Iran’s marginal role in global value chains, with high reliance on domestic inputs and minimal participation in cross-border production fragmentation. This limited integration was more pronounced when compared to countries like China, Korea, and Turkey. To enhance Iran’s role in GVCs, policy measures should focus on reducing dependence on imports of final goods, boosting intermediate goods production, and fostering industrial linkages with BRICS and SCO countries. Incorporating such insights into trade andindustrial policy could help mitigate vulnerability to external shocks and promote sustainable economic growth.
Ali Hasanvand; Bahar Salarvand
Abstract
This study examines the determinants of the ecological footprint in the N11 countries—Bangladesh, Egypt, Indonesia, Iran, South Korea, Mexico, Nigeria, Pakistan, the Philippines, Turkey, and Vietnam—over the period 2000–2022. The main objective of the study is to test the N‑shaped ...
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This study examines the determinants of the ecological footprint in the N11 countries—Bangladesh, Egypt, Indonesia, Iran, South Korea, Mexico, Nigeria, Pakistan, the Philippines, Turkey, and Vietnam—over the period 2000–2022. The main objective of the study is to test the N‑shaped Environmental Kuznets Curve (EKC) hypothesis and to analyze the role of natural resource rents and economic globalization, with particular emphasis on the heterogeneity of effects across different levels of environmental pollution. To achieve this objective, the Method of Moments Quantile Regression (MMQR) is employed for the 10th, 25th, 50th, 75th, and 90th percentiles, and to assess the robustness of the results, panel regression with Driscoll–Kraay standard errors is applied. The empirical findings provide strong evidence in favor of an N‑shaped relationship between economic growth and the ecological footprint. Specifically, in the early stages of development, GDP growth leads to increased environmental degradation; after passing the first turning point, a temporary reduction in pollution occurs; and ultimately, beyond the second turning point, further economic growth once again increases the ecological footprint. The results also reveal substantial heterogeneity in the impact of natural resource rents: this variable has a positive and statistically significant effect on the ecological footprint at lower pollution quantiles, but its magnitude diminishes as pollution levels rise and becomes insignificant at higher quantiles. In contrast, economic globalization exerts a negative and statistically significant effect on the ecological footprint across all quantiles, supporting the pollution halo hypothesis and rejecting the pollution haven hypothesis. The results from the Driscoll–Kraay model further confirm the robustness of these findings. Accordingly, the study recommends the adoption of environmental policies tailored to countries’ pollution levels, alongside energy transition, structural reforms, and the targeted use of economic globalization.
Introduction
Natural resources play a fundamental role in the economic sectors of every country. Proper utilization of these resources can significantly contribute to national economic development. The N11 countries, which are developing nations rich in natural resources, are expected to emerge as economic leaders in the near future (Shahbaz, 2019). These nations have maintained high levels of economic growth and industrialization, which in turn have increased energy demand, primarily supplied from non-renewable sources (Khan et al., 2022).
Consequently, non-renewable resources, while boosting GDP, simultaneously degrade environmental quality (Shehzad et al., 2022). Multiple studies have documented that natural resources are crucial for increasing GDP (Epo & Faha, 2020). Financial advancement facilitates infrastructure development, reduces poverty, and maximizes employment opportunities; however, rapid economic growth can have adverse effects on environmental quality (Zhou et al., 2024). Several countries have exploited natural resources excessively, leading to environmental degradation and climate deterioration (Danish et al., 2020). Research by Muhammad et al. (2021) confirmed that natural resource exploitation harms the environment in BRICS countries, while Shittu et al. (2021) found that natural resources and GDP growth contribute to an increasing ecological footprint in 45 countries. Similarly, Nathaniel et al. (2021) showed that resource dependence elevates greenhouse gas emissions.
Therefore, reliance on natural resources in N11 countries can be an obstacle to sustainable development. Nonetheless, studies by Shehzad et al. (2020, 2021) indicated that GDP growth can coexist with environmental sustainability, supporting the Environmental Kuznets Curve (EKC) hypothesis. Conversely, Narayan et al. (2016) found that EKC is valid only in a limited number of economies, suggesting no general consensus. Thus, highlighting the impact of natural resources on the environment, considering GDP growth in the N11 countries, is essential.
Alongside economic growth, globalization also plays a significant role in environmental degradation. Globalization intensifies trade and production, increasing energy consumption and environmental pressure. N11 countries are consuming large amounts of oil, coal, and gas, further contributing to climate deterioration (Zhou et al., 2024). The N11 countries—Egypt, Bangladesh, Indonesia, Mexico, Iran, Nigeria, the Philippines, Pakistan, South Korea, Vietnam, and Turkey—form a coalition with coordinated financial policies recognized by the IMF. While they are expected to lead global economic development, these nations currently face severe environmental challenges and rank among the most polluted countries. The Ecological Footprint (EF) index has generally increased in these countries over the study period (2000–2022), indicating that economic growth and development often come at the cost of environmental sustainability. For instance, South Korea’s EF rose from 4.39 to 4.53 global hectares per capita, reflecting high consumption and production patterns, followed by Iran and Turkey, with EF increases from 2.53 to 3.3 and from 2.54 to 2.95, respectively. Vietnam experienced a particularly sharp increase from 0.82 to 2.08. Conversely, Mexico reduced its EF from 2.52 to 2.01, while Pakistan and the Philippines maintained relatively low and stable EF levels (0.78 and 0.94, respectively).
This research emphasizes the importance of sustainable economic development in N11 countries, highlighting the environmental consequences of resource extraction. The study aims to identify the role of natural resources in environmental degradation, assess the contribution of globalization, and examine the N-shaped EKC hypothesis in these countries.
Questions
The main research questions are: (1) Does natural resource rent deteriorate environmental quality in N11 countries? (2) Can globalization improve environmental quality? (3) Does the N-shaped EKC hold in these countries?
Methods and Material
This study investigates the relationship between natural resource rent, globalization, GDP, and ecological footprint in N11 countries. Annual data for 2000–2022 were collected, excluding Nigeria due to data unavailability. GDP and natural resource rent data were obtained from the World Bank, while globalization and EF data were sourced from the KOF Institute and Global Footprint Network, respectively. Table 1 presents detailed variables and sources.
GDP represents per capita economic output, NAT captures income from natural resource exploitation, EG measures globalization through investment, trade, and technology interdependence, and EF evaluates environmental impact by quantifying required biological resources to support consumption and waste. All variables are logarithmically transformed for regression analysis. The model is defined as
(1)
(2)
Where i=1,…,N denotes countries and t=1,…,T denotes years. MMQR (Machado & Silva, 2019) was applied to estimate conditional quantiles at 10th, 25th, 50th, 75th, and 90th percentiles, allowing a detailed assessment of heterogeneous effects. Driscoll-Kraay panel regression was also employed to validate results under potential cross-sectional dependence and heteroskedasticity.
Results and Discussion
The MMQR results reveal an inverted N-shaped relationship between GDP and EF, confirming the N-shaped EKC hypothesis for N11 countries. The coefficients of lnGDP, lnGDP², and lnGDP³ were positive, negative, and positive, respectively, across all quantiles and in the Driscoll-Kraay panel model (β = 0.58, -1.91, 0.07). This indicates that environmental degradation initially rises with economic growth (scale effect), temporarily decreases with technological and efficiency improvements (composition and technique effects), but may increase again at very high income levels.
Globalization consistently exhibits a negative and significant effect on EF across all quantiles, with stronger reductions observed at higher EF levels (from -0.94 at the 10th percentile to -1.07 at the 90th percentile), suggesting that global integration promotes cleaner technology adoption and environmental standards.
Natural resource rents positively affect EF, especially in lower and middle quantiles. The highest effect occurs at the 10th percentile (β = 0.10) and diminishes toward the 90th percentile (β = 0.02, not significant), indicating that resource dependence drives environmental pressure mainly in early and intermediate development stages. The Driscoll-Kraay panel confirms a positive and significant mean effect (β = 0.06).
Policy implications include: (1) managing economic growth with stringent environmental regulations, (2) diversifying away from natural resource dependence through investment in sustainable infrastructure and renewable technology, (3) leveraging globalization to promote green investment and international environmental standards, and (4) tailoring policies according to pollution levels, recognizing heterogeneous impacts across quantiles.
Conclusion
This study demonstrates that N11 countries face significant environmental challenges despite rapid economic growth. The N-shaped EKC confirms that high-income growth may again increase ecological pressure. Resource dependence exacerbates environmental degradation, while globalization offers a pathway to mitigate such effects. Sustainable development in N11 countries requires coordinated policies balancing economic growth with environmental stewardship, strategic investment in technology, and intelligent use of global integration to achieve long-term ecological sustainability.
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