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اثرگذاری پیچیدگی اقتصادی و نهادهای دولتی بر رشد اقتصادی کشورهای منتخب در حال توسعه | ||
| مدیریت سازمانهای دولتی | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 11 شهریور 1405 اصل مقاله (1.75 M) | ||
| نوع مقاله: علی | ||
| شناسه دیجیتال (DOI): 10.30473/ipom.2026.76598.5275 | ||
| نویسندگان | ||
| علیرضا کشفی1؛ علی سلمانپور* 2؛ سیما اسکندری3 | ||
| 1گروه علوم اقتصادی، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران. | ||
| 2گروه علوم اقتصادی، واحد مرند دانشگاه آزاد اسلامی، مرند، ایران. | ||
| 3گروه علوم اقتصادی، واحد میانه، دانشگاه آزاد اسلامی، میانه، ایران | ||
| چکیده | ||
| این مقاله به بررسی اثرگذاری غیرخطی پیچیدگی اقتصادی و نهادهای دولتی بر رشد اقتصادی کشورهای منتخب در حال توسعه، با تأکید بر نقش آستانهای رانت منابع طبیعی میپردازد. روششناسی مقاله حاضر از نوع کاربردی و با روش توصیفی-تحلیلی است. جامعه آماری تحقیق شامل 31 کشور در حال توسعه تولیدکننده علم طی دوره زمانی 2023-2008 میباشد. برای تجزیه و تحلیل دادهها و برآورد مدل از روش رگرسیون آستانهای پانل (PSTR) استفاده شده است. در این مدل، رانت منابع طبیعی بهعنوان متغیر انتقال و آستانه در نظر گرفته شده است. نتایج تحقیق وجود یک رابطه غیرخطی و آستانهای را تأیید میکند که منجر به شناسایی دو رژیم اقتصادی متمایز میشود. در رژیم پایین (وابستگی کم به رانت منابع): افزایش پیچیدگی اقتصادی، بهبود کیفیت نهادها و سرمایه انسانی تأثیر مثبت و معناداری بر رشد اقتصادی دارند. در رژیم بالا (وابستگی زیاد به رانت منابع) تأثیر پیچیدگی اقتصادی بر رشد اقتصادی منفی و معنادار میشود که نشاندهنده پدیده «بیماری هلندی» است. در این رژیم، نقش نهادهای قوی و سرمایه انسانی بهطور قابلتوجهی تقویت میشود، بهطوری که میتوانند اثرات مخرب رانت را خنثی و آن را به عاملی برای رشد تبدیل کنند. اثر مخارج تحقیق و توسعه (R&D) در هیچ یک از رژیمها معنادار نبود. یافتهها نشان میدهد که وجود نهادهای قوی، شرط لازم اساسی برای دستیابی به پیچیدگی اقتصادی مثبت و رشد پایدار، بهویژه در کشورهای دارای منابع طبیعی است. حرکت به سمت پیچیدگی اقتصادی به صورت خودکار منجر به تقویت نهادها نمیشود و در غیاب نهادهای کارآمد، وفور منابع طبیعی میتواند اثرات توسعهبخش پیچیدگی اقتصادی را خنثی یا حتی معکوس نماید. | ||
| کلیدواژهها | ||
| پیچیدگی اقتصادی؛ نهادهای دولتی؛ رشد اقتصادی؛ رگرسیون آستانهای (PSTR)؛ کشورهای در حال توسعه | ||
| عنوان مقاله [English] | ||
| The Impact of Economic Complexity and Government Institutions on Economic Growth in Selected Developing Countries | ||
| نویسندگان [English] | ||
| Alireza Kashfi1؛ Ali Salmanpur2؛ Sima Eskandari3 | ||
| 1Department of Economics, Mi.C., Islamic Azad University, Miyaneh, Iran. | ||
| 2Department of Economics, Mi.C., Islamic Azad University, Marand, Iran. | ||
| 3Department of Economics, Mi.C., Islamic Azad University, Miyaneh, Iran. | ||
| چکیده [English] | ||
| Introduction The quest for sustained economic development remains the central preoccupation of policymakers in developing nations. Traditional neoclassical growth models, such as the Solow-Swan framework, primarily attribute economic growth to factor accumulation—specifically capital and labor inputs. However, contemporary evolutionary and endogenous growth theories have shifted the focus toward the “composition” of production. In this paradigm, economic complexity—defined as the diversity and sophistication of a country’s export basket and production capabilities—is identified as a critical determinant of long-term prosperity. A nation’s ability to export complex products reflects the underlying collective knowledge, skills, and organizational capabilities embedded within its economic system. Despite the proven relationship between economic complexity and growth, recent empirical discourse has identified a “missing link”: the institutional environment. It is argued that production complexity cannot yield its full potential in a vacuum. Effective government institutions—encompassing regulatory quality, the rule of law, control of corruption, and political stability—are necessary to provide the predictable environment required for high-tech industrial activity. Without sound institutions, complex economic structures may remain fragile or fail to generate positive spillovers. This study seeks to bridge this gap by investigating the interplay between economic complexity and government institutions. Specifically, it tests the hypothesis that the relationship between economic complexity and economic growth is not linear but conditioned by the quality of a country’s institutional framework. Using a Panel Smooth Transition Regression (PSTR) model, this research examines whether government institutions serve as a threshold that determines the efficacy of economic complexity as a growth driver in developing countries from 2008 to 2023. Methodology To rigorously evaluate these complex, non-linear dynamics, the study employs the Panel Smooth Transition Regression (PSTR) approach. Unlike standard linear panel models, PSTR is uniquely suited for this research because it allows for the coefficients of the explanatory variables to change continuously as a function of a “threshold variable.” In this model, the threshold variable is represented by the index of Government Institutional Quality. The dataset comprises a selection of developing countries over the period 2008–2023, ensuring sufficient temporal coverage to observe structural economic changes. The dependent variable is the rate of real GDP per capita growth, representing sustained economic expansion. The core independent variables are Economic Complexity Index (ECI): A measure of the diversity and ubiquity of products in a country’s export basket. Institutional Quality Indices: An aggregate measure derived from standardized international datasets reflecting government effectiveness, regulatory quality, and the rule of law. The PSTR methodology enables the model to identify “regimes.” By estimating a transition function, the research determines the threshold level of institutional quality required for economic complexity to become an effective engine of growth. This econometric technique effectively addresses endogeneity issues and accounts for the heterogeneous nature of developing economies, where some nations possess the capacity to absorb complex technologies while others struggle due to institutional bottlenecks. Findings The empirical results derived from the PSTR model provide compelling evidence of a non-linear, threshold-dependent relationship. The findings are summarized as follows: First, the analysis confirms that economic complexity is a positive predictor of growth, but its impact is significantly mediated by the quality of state institutions. In environments characterized by low institutional quality, the marginal effect of economic complexity on economic growth is observed to be negligible or statistically weak. This suggests that in the absence of a stable regulatory and legal environment, the introduction of complex production activities fails to generate the desired growth trajectories. Second, the model identifies a clear institutional threshold. Once a country’s institutional quality crosses a critical “tipping point,” the growth-enhancing impact of economic complexity increases substantially. Beyond this threshold, the “spillover effects” of complex knowledge become more pronounced, as high-quality institutions facilitate the flow of capital, protect intellectual property, and incentivize technological innovation. Third, the findings indicate that for developing nations, a strategy of industrial diversification is incomplete without concurrent institutional reform. Countries that attempted to increase their economic complexity without addressing systemic institutional weaknesses experienced lower-than-expected growth outcomes. Conversely, nations that prioritized institutional stability were able to leverage their production capabilities far more efficiently, resulting in faster structural transformation and resilient growth. Discussion and Conclusion The results of this study carry profound policy implications. The central conclusion is that economic complexity and government institutions are complements, not substitutes. Policymakers in developing countries often pursue industrial policies focused solely on export diversification or technology adoption. However, this research demonstrates that such efforts may yield suboptimal results if the underlying “rules of the game”—the institutional framework—are not robust. Policy Recommendations: Institutional Sequencing: Governments should prioritize institutional reforms—specifically enhancing regulatory quality and the rule of law—as a prerequisite for or alongside industrial policy initiatives. Strengthening these “soft” infrastructures is essential to make “hard” investments in industrial complexity effective. Capacity Building: Developing nations must foster a regulatory envirnment that reduces transaction costs and minimizes corruption, as these are the primary factors that dampen the growth-promoting effects of economic complexity. Holistic Development: Development strategies should transition from being purely sectoral (focusing on specific industries) to being institutional (focusing on the governance capacity to support those industries). In conclusion, this research provides a nuanced understanding of the mechanics of economic growth in developing nations. By demonstrating that institutional quality acts as a threshold that dictates the success of economic complexity, the study offers a roadmap for more effective development strategies. Future research should further investigate the role of human capital in this institutional-complexity nexus to determine how educational infrastructure interacts with these dynamics to drive long-term prosperity. | ||
| کلیدواژهها [English] | ||
| Economic Complexity, State Institutions, Economic Growth, Panel Smooth Transition Regression (PSTR), Developing Countries | ||
| مراجع | ||
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Agu, C., Ogbuabor, J. E., & Onah, B. U. (2024). How are economic governance institutions moderating the effect of economic complexity on trade, FDI inflow, environmental degradation, and economic growth in Africa? The Journal of the Knowledge Economy, 16(2), 9536–9567. https://doi.org/10.1007/s13132-024-02284-2 Ahmadian, M.M., Aghajani, H.A., Shirkhodaie, M., & Tehranchian, A.M. (2019). Economic complexity as a new approach to assessing the commercialization of scientific and technological products. Library and Information Sciences, 21(4), 124-161. (In Persian) DOI: 10.30481/lis.2019.79477 Azimi, N.A. (2018). The effect of knowledge based economic indicators on the countries' economic complexity. Research and Planning in Higher Education, 24(4), 1-23. (In Persian) Canh, N. P., & Thanh, S. D. (2020). Financial development and the shadow economy: A multi-dimensional analysis. Economic Analysis and Policy, 67, 37-54. https://doi.org/10.1016/j.eap.2020.05.002 Cozzens, S. E., Bobb, K., & Bortagaray, I. (2002). Evaluating the distributional consequences of science and technology policies and programs. Research Evaluation, 11(2), 101-107. Dadgar, Y., Nazari, R., Fahimi Far, (2024). Investigating Iran's Economic Complexity Index and Factors Affecting It: Basic Knowledge in Export. New Approaches in Management and Marketing, 2(2), 24-31. (In Persian) https://doi.org/10.22034/jnamm.2024.428345.1035 Dogan, B., Ghosh, S., & Shahbaz, M. (2020). Does economic complexity matter for environmental degradation? An empirical analysis for different stages of development. Environmental Science and Pollution Research, 27(26), 32700–32712. https://doi.org/10.1007/s11356-020-09410-y Dogan, B., Madaleno, M., & Tiwari, A. K. (2021). Does economic complexity influence environmental performance? Evidence from OECD countries. Journal of Cleaner Production, 291, 125827. https://doi.org/10.1016/j.jclepro.2021.125827 Emadifar, F., & Tabatabaei-Nasab, Z. (2015). Effects of Economic Complexity on Economic Growth: A Case Study of ECO Member Countries. The Third International Conference on Economics, Management, and Accounting with an Approach to Value Creation. (In Persian) Gómez-Zaldívar, M., Fonseca, F. J., Mosqueda, M. T., & Gómez-Zaldívar, F. (2020). Spillover effects of economic complexity on the per capita GDP growth rates of Mexican states, 1993–2013. Estudios de Economía, 47(2), 221–243. https://doi.org/10.4067/S0718-52862020000200221
Han, J., & Shen, Y. (2015). Financial development and total factor productivity growth: Evidence from China. Emerging Markets Finance and Trade, 51(Suppl. 1), S261–S274. https://doi.org/10.1080/1540496X.2014.998928 Hartmann, D., Guevara, M. R., Jara-Figueroa, C., Aristarán, M., & Hidalgo, C. A. (2017). Linking economic complexity, institutions, and income inequality. World Development, 93, 75–93. https://doi.org/10.1016/j.worlddev.2016.12.020 Hausmann, R., & Hidalgo, C. A. (2011). The network structure of economic output. Journal of Economic Growth, 16(4), 309–342. https://doi.org/10.1007/s10887-011-9071-4 Hausmann, R., & Hidalgo, C. A. (2013). The atlas of economic complexity: Mapping paths to prosperity. MIT Press. Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Chung, S., Jimenez, J., Simoes, A., & Yildirim, M. A. (2014). The atlas of economic complexity: Mapping paths to prosperity. MIT Press. Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570–10575. https://doi.org/10.1073/pnas.0900943106 Javaheri, B., Ghaderi, S., Ghomashi, N., & Amani, R. (2024). Investigating the impact of economic complexity and ecological footprint on economic growth in OPEC countries. Economic Research and Perspectives, 24(1), 27-56. (In Persian) DOI: 10.22034/24.1.27 Khaki, N., Khorsandi, M., Mohammadi, T., Faridzad, A., & Azizi, Z. (2023). The Impact of Energy Consumption Structure on Pollution Emissions in Industrialized and Developing Countries: A panel Smooth Transition Regression (PSTR) Approach. Quarterly journal of Industrial Economics Reseaches, 6(22), 51-64. (In Persian) DOI: 10.30473/jier.2023.66034.1354 Lapatinas, A., Litina, A., & Poulios, K. (2019). Economic complexity and environmental performance: Evidence from a world sample. Environmental and Resource Economics, 74(2), 713–735. https://doi.org/10.1007/s10640-019-00347-6 Leukaus, C., & Horng, M. (2020). Institutions, economic complexity, and economic development: A review. Journal of Economic Surveys, 34(5), 1165–1193. https://doi.org/10.1111/joes.12370 Mealy, P., & Teytelboym, A. (2020). Economic complexity and the green economy. Research Policy, 49(8), 103948. https://doi.org/10.1016/j.respol.2020.103948 Mini, L., Moyo, C., & Phiri, A. (2024/2025). Morais, J., Pires, A. J. G., & Rodrigues, P. M. M. (2021). Economic complexity and economic growth: A panel data analysis. Empirical Economics, 60(3), 1317–1337. https://doi.org/10.1007/s00181-020-01828-0 Naghavi, A., & Todaro, M. P. (2019). Economic complexity and energy consumption: A cross-country analysis. Energy Economics, 84, 104545. https://doi.org/10.1016/j.eneco.2019.104545 Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. https://doi.org/10.1287/orsc.5.1.14 North, D. C., & Thomas, R. P. (1973). The rise of the western world: A new economic history. Cambridge University Press. Ranjbar, O., Sagheb, H., & Ziaee Bigdeli, S. (2019). Analyzing Dynamism in Iran’s Non-Oil Exports: New Evidence Using Economic Complexity Theory, Journal of Economic Research, 54(126), 47-73. (In Persian) DOI: 10.22059/jte.2019.256270.1007898 Saeidi, SH., Samsami, H., & Davoodi, P. (2022). Investigating the Effects of Institutional Factors and Human Capital on Economic Growth. Journal of Economics & Modelling, 13(1), 119-151. (In Persian)DOI: 10.48308/jem.2022.225061.1699 Şanlı, D., Yiğiteli, N. G., & Tatar, H. E. (2024). Santoalha, A., & Boschma, R. (2020). Diversifying in green technologies: European regions and the growth of new technological domains. Economic Geography, 96(2), 161–188. https://doi.org/10.1080/00130095.2020.1715787 Sayehmiri, A., Latifi, J., Shirkhani, A., & Seyfi, F. (2026). Vahid Zarei 5Examining the Role of Institutional Quality in Moderating the Effects of Economic Policy Uncertainty on Economic Growth in Iran. Economic Research and Perspectives, 26(1), 331-356. (In Persian) https://doi.org/10.48311/ecor.2025.27946 Sepehrdoust, H., Davarikish, M., & Setarehie, M. (2020). Role of Financial Policies in Economic Complexity: Baumol’s Unbalanced Growth Theory Assessment. Quarterly Journal of Quantitative Economics, 17(3), 117-143. (In Persian) https://doi.org/10.22055/jqe.2019.28752.2045 Setojski, M., & Kukaro, J. (2017). Economic complexity and growth in Central and South-Eastern Europe. Eastern European Economics, 55(5), 427–447. https://doi.org/10.1080/00128775.2017.1346459 Shahabadi, A., & Arghand, H. (2019). The Effects of Economic Complexity on Social Welfare in Selected Developing Countries. Journal of Trade Studies, 23(89), 89-122. (In Persian) DOR: 20.1001.1.17350794.1397.23.89.4.2 Shahmoradi, B., & Sadeghi Siahkali, M. (2018). Identifying the Level of Productive Knowledge in Iran 2025 using Economic Complexity Approach, Iranian Economic Development Analyses, 5(3), 29-50. (In Persian) DOI: 10.22051/edp.2018.19154.1140 Smith, A. (1776). An inquiry into the nature and causes of the wealth of nations. W. Strahan and T. Cadell. Sorkhedehi, F., & Kavianinia, P. (2024). Investigating the Asymmetric Effects of Renewable Energy and Economic Complexity on Iran’s Economic Growth within the NARDL Framework. Economics Research, 24(93), 124-158. (In Persian) https://doi.org/10.22054/joer.2025.83642.1246 Stojkoski, V., & Kocarev, L. (2016). The relationship between economic complexity and economic growth: A review. Physica A: Statistical Mechanics and its Applications, 462, 762–781. https://doi.org/10.1016/j.physa.2016.06.101 Williamson, O. E. (1985). The economic institutions of capitalism. Free Press. Yahyazadefar, M., Shababi, H., Rasekhi, S., & Shirkhodaei, M. (2017). The Interpretive-Structural Model for Prioritize the Relationship among Effective Factors on Science Development, Technology Development and Economic Growth in Iran, Journal of Science & Technology Policy, 10(3), 77. (In Persian) DOI: 20.1001.1.20080840.1396.10.3.7.0 Yalta, A. Y., & Yalta, T. (2021). Determinants of economic complexity in MENA countries. JOEEP: Journal of Emerging Economies and Policy, 6(1), 5–16. Zhu, S., & Li, R. (2017). Economic complexity, human capital and economic growth: Empirical research based on cross-country panel data. Applied Economics, *49*(38), 3815–3828. https://doi.org/10.1080/00036846.2016.1270413 Zhu, S., Li, J., & Lee, C. C. (2023). National innovation systems, economic complexity, and economic growth: Evidence from patent data. Technological Forecasting and Social Change, 186, 122128. https://doi.org/10.1016/j.techfore.2022.122128 | ||
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