نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد اقتصاد، گروه اقتصاد، دانشکده علوم اجتماعی و اقتصادی، دانشگاه الزهرا (س)، تهران، ایران

2 دانشجوی دکتری اقتصاد بخش عمومی، گروه اقتصاد، دانشکده علوم اجتماعی، اقتصاد و کارآفارینی، دانشگاه رازی، کرمانشاه، ایران.

3 کارشناس ارشد علوم اقتصادی، گروه اقتصاد، دانشکده علوم اجتماعی و اقتصادی، دانشگاه الزهرا (س)، تهران، ایران.

چکیده

چکیده گسترده
معرفی:
 نرخ بالای ﺗﻮﺭﻡ معضل اقتصادی مهمی در کشورهای درحال توسعه از جمله ایران است که با وجود پیشینه طولانی تحلیل و بررسی کماکان مورد بحث است و جزء دغدغه‌های اصلی سیاست‌مداران و اقتصاددانان به شمار می‌رود. براساس شواهد موجود تورم دارای آثار نامطلوبی بر جامعه است بطوری که اقتصاددانان معتقدند هزینه‌هایی که تورم بر جامعه تحمیل می‌کند می‌تواند بسیار جدی‌تر از هزینه‌های ناشی از کند شدن رشد اقتصادی باشد.
  با عنایت به اثرات منفی تورم، عوامل مؤثر در ایجاد و تشدید آن در مکاتب مختلف مورد توجه قرار گرفته است. در این خصوص بر اساس مباحث نظری مطرح شده تورم دارای سه منشاء عمده (1) افزایش تقاضا، (2) فشار هزینه و (3) تنگناهای ساختاری است. یکی از مهمترین سیاست‌های کاهش تورم، افزایش عرضه و رشد محصول است. در این راستا پیچیدگی اقتصادی می‌تواند از طریق افزایش ظرفیت و تنوع تولید محصولات پیچیده، باعث شکل گیری مازاد عرضه و در نهایت کاهش تورم در اقتصاد شود.  بر اساس آخرین رتبه‌بندی شاخص پیچیدگی اقتصادی که در سال 2018 توسط دانشگاه هاروارد، برای 133 کشور جهان گزارش شده است، اختلاف چشمگیری میان کشورهای توسعه یافته و در حال توسعه وجود دارد.
 
 متدولوژی:
هدف از مطالعه حاضر بررسی تأثیر پیچیدگی اقتصادی بر تورم در کشورهای عضو سازمان همکاری اسلامی بر اساس رویکرد بین کشوری طی دوره 2018-1995 است. اطلاعات مورد نیاز از درگاه بانک جهانی و اطلس پیچیدگی اقتصادی جهان دریافت گردید. محدوده مکانی این پژوهش سی کشور منتخب عضو سازمان همکاری اسلامی است که با توجه به محدودیت آماری دادهها و شواهد تاریخی مشابه انتخاب شده است.
تصریح مدل پژوهش
با توجه به مبانی نظری و مطالعات تجربی، الگوی تصریح شده در این پژوهش به صورت رابطه زیر تصریح شد:
INF_it=C+β_1*INF_(it-1)+β_2*(M2gr_it-GDPgr_it)+β_3*NAT_it+β_4*ECI_it+ε_i

در این مدل i:کشورها، t: زمان . C: عرض از مبدأ و β: ضرایب متغیرهای توضیحی (ضرایب شیب) می‌باشد. تورم: (INF). تورم دوره قبل :(INF-1). رشد نقدینگی: (M2gr). نرخ رشد اقتصادی: (GDPgr). وفور منابع طبیعی: (NAT). شاخص پیچیدگی اقتصادی: (ECI). مدل GMM جهت تخمین این پژوهش انتخاب شده است.
 
یافته­ ها:
با توجه به نتایج حاصل از این پژوهش ، تأثیر عوامل اقتصادی بر تورم در  کشورهای منتخب برآورد شد. ضریب متغیر اصلی مدل تصریح‌شده یعنی شاخص پیچیدگی اقتصادی ECI، منفی و به لحاظ آماری در سطح 5% معنی‌دار است دیگر متغیرهای توضیحی مدل که در سطح پنج درصد معنی‌دار بودند و همگی دارای اثر مثبت بر تورم بودند عبارت‌اند از تورم انتظاری، تفاوت نرخ رشد نقدینگی با رشد اقتصادی  و وفور منابع طبیعی.
 
نتیجه:
 نتایج حاصل از تحلیل یافته‌های مدل نشان داد که فرضیه کاهش نرخ تورم از طریق پیچیدگی اقتصادی در کشورهای منتخب اسلامی برقرار است. همچنین مشخص شد با افزایش تورم انتظاری، تفاوت نرخ رشد نقدینگی با رشد اقتصادی و ثروتهای طبیعی، تورم هم افزایش مییابد. به این ترتیب نتایج حاصل از برآورد الگو گویای آن است که ضرایب برآورد شده تمامی متغیرها از حیث علامت با مبانی نظری سازگار هستند. بنابراین پیشنهاد می شود:
سیاستگذاران و تصمیم گیرندگان اقتصادی، تحقیقات انجام شده در مورد شاخصهای پیچیدگی و فضای محصولات را مورد توجه قرار داده و ﺳﯿﺎﺳﺖﻫﺎ و ﺗﺪاﺑﯿﺮ ﻻزم ﺑﺮای ﺑﺴﺘﺮﺳﺎزی ﻣﺤﺼﻮﻻت ﻓﻨﺎوراﻧﻪ ﺑﺎ ﭘﯿﭽﯿﺪﮔﯽ ﺑﺎﻻﺗﺮ ﺑﺎ ﻫﺪف ﺗﻨﻮعﺑﺨﺸﯽ ﺑﻪ ﻣﺤﺼﻮﻻت رﻗﺎﺑﺘﯽ ﮐﺸﻮرهای اسلامی را اﺗﺨﺎذ کنند که البته در اﯾﻦ ﻣﺴﯿﺮ ﻻزم اﺳﺖ ﮐﻪ اﺑﺘﺪا قابلیتﻫﺎی ﻓﻨﺎوراﻧﻪ ﮐﺸﻮرها ﺷﻨﺎﺳﺎﯾﯽ ﺷﻮد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The Impact of Economic Complexity on Inflation in the Selected Countries of Organization of Islamic Cooperation

نویسندگان [English]

  • Abolfazl Shahabadi 1
  • Bahareh Karami 2
  • Hanieh Arghand 3

1 Professor of Economics, Department of Economics, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

2 PhD Student in Public Sector Economics, Department of Economics, Faculty of Social Sciences, Economics and Entrepreneurship, Razi University, Kermanshah, Iran.

3 Master of Economics, Department of Economics, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran.

چکیده [English]

EXTENDED ABSTRACT
INTRODUCTION
high inflation rate is an important economic problem in developing countriesincluding Iran, which, despite its long history of analysis, is still under discussion and is one of the main concerns of politicians and economists. According to the available evidence, inflation has adverse effects on society and economists believe that the costs that inflation imposes on society can be much more serious than the costs of slowing the economic growth. Considering the negative effects of inflation, the effective factors of creating and intensifying inflation have been studied in different schools. In this regard, according to the theoretical issues, inflation has three main sources of 1) increasing demand, 2) cost pressure and 3) structural bottlenecks. One of the most important policies to reduce inflation is to increase the product's supply and growth. In this regard, economic complexity can lead to the formation of oversupply and ultimately reduce inflation in the economy through increasing the capacity of production and diversifying the complex products' production. According to the latest ranking of the Economic Complexity Index reported in 2018 by Harvard University for 133 countries, there is a significant difference between developed and developing countries.
 
METHODOLOGY
The purpose of this study is to investigate the effect of economic complexity on inflation in OIC member countries based on the inter-country approach during the period 1995-2018. The required information was obtained from the World Bank and the Atlas of World Economic Complexity. The geographical scope of this study is thirty selected member countries of the Islamic Cooperation Organization, which have been selected due to the statistical limitations of similar data and historical evidence.
 
Specifying research model
According to the theoretical foundations and experimental studies, the model specified in this study was specified as follows:
 
INF_it=C+β_1*INF_(it-1)+β_2*(M2gr_it-GDPgr_it)+β_3*NAT_it+β_4*ECI_it+ε_i

In this model i: country, t: time, C: the width of the origin and β: the coefficients of the explanatory variables (slope coefficients). (INF): Inflation Rate. (INF-1): Inflation of the previous period. (M2gr): growth of liquidity. (GDPgr): growth of gross domestic production. (NAT): abundance of the natural resources. (ECI): Index of economic complexity.
The GMM model is selected to estimate this research.
 
FINDINGS
According to the results of this study, the impact of economic factors on inflation in selected countries was estimated. The coefficient of the main variable of the stipulated model, ie the ECI economic complexity index, is negative and statistically significant at the 5% level. Other explanatory variables of the model, which were significant at the 5% level and all had a positive effect on inflation, are expected inflation, difference between the growth of liquidity and the economic growth and abundance of natural resources.
 
CONCLUSION
The results of the analysis of the model findings showed that the hypothesis of reducing inflation through economic complexity is established in selected Islamic countries. It was also found that with increasing expected inflation, the difference between the growth rate of liquidity and economic growth and natural wealth, inflation increases. Thus, the results of model estimation show that the estimated coefficients of all variables are signally compatible with theoretical foundations. Therefore it is suggested:
Policymakers and economic decision-makers should consider research on the indicators of complexity and product space, And adopt the necessary policies and measures to pave the way for higher-tech technological products with the aim of diversifying the competitive products of Islamic countries. Of course, it is necessary to first identify the technological capabilities of countries in this direction.

کلیدواژه‌ها [English]

  • Inflation
  • Economic Complexity
  • Expected Inflation
  • Liquidity Growth
  • Economic Growth
Adam, A., Garas, A., Katsaiti, M. S., & Lapatinas, A. (2021). Economic complexity and jobs: an empirical analysis. Economics of Innovation and New Technology, 1-28.
Ahmadzadeh, K. & Nasri, S. (2021). Investigating the welfare losses of commodity inflation in the fourth and fifth development plans for selected provinces of Iran. Quarterly Journal of Quantitative Economics (JQE), 18(3), 99-134. doi: 10.22055/jqe.2019.29026.2059 (In Persian)
Amiri, B. (2017). The Effect of Governance Index on Inflation in Selected Countries of G77. Quarterly Journal of Quantitative Economics(JQE), 14(3), 161-185. doi: 10.22055/jqe.2017.18817.1448 (In Persian)
Armen, S. A., Ghorbannezhad, M., & Kafili, V. (2017). Take another look at inflation: VARX approach. Iranian Scientific Magazine of Applied Economic Studies, 6(22), 99-121. URL: https://aes.basu.ac.ir/article_1882_en.html?lang=fa (In Persian)
Azimi, S. R, Miri, A. A, Taghizadeh, K. & Samadi, R. (2013). the Study of Trend and Causes of Iran’s Inflation During (2010 -2012) and Measures Fulfilled to Subdue it. Quarterly Journal of Fiscal and Economic Policies (qjfep). 1(1), 25-58. URL: http://qjfep.ir/article-1-22-en.html (in persian)
Azizi, Z., & Pedram, M. (2019). The Role of Export Diversification on the Relationship between Trade Openness and Volatility of Economic Growth in Selected Developing Countries (1980-2015). Iran Economic Research Journal, 23(77), 107-138. URL: https://ijer.atu.ac.ir/article_10149.html (In Persian)
Bala, U., Chin, L. E. E., Kaliappan, S. R., & Ismail, N. W. (2017). The impacts of oil export and food production on inflation in African OPEC members. International Journal of Economics and Management, 11 (S3), 573-590.
Buchheim, V., & Kedert, M. (2016). Digitization effect on the inflation rate: An empirical analysis of possible digitization channels. Available at SSRN: http://www.divaportal.org/smash/record.jsf?pid=diva2%3A948969&dswid=-4271
Chowdhury, A. (2014). Inflation and inflation-uncertainty in India: the policy implications of the relationship. Journal of Economic Studies, 41(1), 71-86.
Cristelli, M., Tacchella, A., & Pietronero, L. (2015). The heterogeneous dynamics of economic complexity. Public Library of Science One, 10(2), e0117174.
Elahi, N., Khodadad Kashi, F., & Sagheb, H. (2018). Technology Content, Sophistication and Revealed Factor Intensities in Export of Iran. Quarterly journal of Industrial Economic Researches, 2(3), 57-70. URL: https://indeco.journals.pnu.ac.ir/article_5286_en.html (In Persian)
Elgammal, M. M., & Eissa, M. A. (2016). Key determinants of inflation and monetary policy in the emerging markets: evidence from Vietnam. Afro-Asian Journal of Finance and Accounting, 6(3), 210-223.
Felipe, J., Kumar, U., Abdon, A., & Bacate, M. (2012). Product complexity and economic development. Structural Change and Economic Dynamics, 23(1), 36-68.
Fortun Vargas, J. M. (2012). Money growth and inflation: evidence from post-inflation Bolivia. International Journal of Economic Policy in Emerging Economies, 5(4), 353-366
Fuhrer, J. C. (1997). The (un) importance of forward-looking behavior in price specifications. Journal of Money, Credit, and Banking, 338-350.
Ghavam, M. Z., & Tashkini, A. (2005). Experimental analysis of inflation in iranian economy (1959-2002), Iranian Journal Of Trade Studies (IJTS),  9(36). URL: https://www.sid.ir/en/journal/ViewPaper.aspx?id=35583 (In Persian)
Granger, C. W., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111-120.
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.
Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Simoes, A., & Yildirim, M. A. (2013). The Atlas of Economic Complexity: Mapping Paths to Prosperity. (B. Shahmoradi, Trans.). Cambridge, MA: Harvard University.
Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570-10575.
Lv, L., Liu, Z., & Xu, Y. (2019). Technological progress, globalization and low-inflation: Evidence from the United States. Public Library of Science One, 14(4), e0215366.
Mousavi, A. K. A., & Taghipour, A. (2001). A review of relationship between export diversification and stability oF export earnings in Iran.    Iranian Journal Of Trade Studies (IJTS), 5(20), 63-94. URL:https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=21765 (In Persian).
Muktadir-Al-Mukit, D., & Shafiullah, A. Z. M. (2014). Export, Import and Inflation: A Study on Bangladesh. Amity Global Business Review, 9. Available at SSRN: https://www.researchgate.net/publication/270450475
Nadiri, M., & Mohammadi, T. (2011). Estimating an institutional structure in economic growth using GMM dynamic panel data method. Economical Modeling, 5(15), 1-24. URL: http://eco.iaufb.ac.ir/article_555516_en.html?lang=fa (In Persian)
Pourkazemi, M. H., Biravand, A., & Delfan, M. (2016). Designing a Warning System for Hyperinflation for Iran’s Economy. Research and Economic Policy Journal, 23(76), 145-166. URL: https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=534342 (In Persian)
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 (Tahghighat-E-Eghtesadi), 54(1), 47-73. URL:  https://jte.ut.ac.ir/article_70071_en.html?lang=en (In Persian)
Saumitra, B., & Raja, S. (2012). A note on excess money growth and inflation dynamics: evidence from threshold regression, MPRA Paper No. 38036.
Shahabadi, A., & Heydarkhani, F. (2020). The Effect of Knowledge-Based Economy Components on Misery Index in Selected Countries. The Journal of Planning and Budgeting, 25(3), 95-116. URL: https://jpbud.ir/browse.php?a_id=1947&sid=1&slc_lang=en (In Persian)
Shahmoradi, B., & Eshtheardi, M. S. A. (2018). Investigating the status of Iran's technological competitiveness in the region, based on the economic complexity approach. Journal of Science and Technology Policy, 10(1), 29-39. URL: https://www.sid.ir/en/Journal/ViewPaper.aspx?ID=747719 (In Persian)
Shakeri, A. (2006). Microeconomics 2 (theories and applications), Tehran: Ney. (In Persian)
Stojkoski, V., & Kocarev, L. (2017). The relationship between growth and economic complexity: evidence from Southeastern and Central Europe. Available at SSRN: https://mpra.ub.uni-muenchen.de/77837/3/MPRA_paper_77837.pdf
Wimanda, R. E., Turner, P. M., & Hall, M. B. (2011). Expectations and the inertia of inflation: the case of Indonesia. Journal of Policy Modeling, 33(3): 426-438.
Zack, M. H. (1999). Developing a knowledge strategy. California Management Review, 41(3), 125-145.
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.