پویایی منطقه‌ای تورم در ایران: الگوی سرایت قیمتی و شناسایی نقش استان‌ها در انتقال تکانه‌ها

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه اقتصادی، پژوهشکده امور اقتصادی، تهران، ایران.

چکیده

در این پژوهش، با استفاده از رویکرد اتصال مشترک توسعه‌یافته که ترکیبی از مدل خودرگرسیون برداری با ضرایب متغیر در زمان (TVP-VAR)، تجزیه واریانس خطای پیش‌بینی تعمیم‌یافته (GFEVD)  و نرمال‌سازی مشترک است به بررسی سرریز تورم میان استان‌های ایران با استفاده از داده‌های شاخص قیمت مصرف‌کننده ماهانه در ۳۱ استان کشور، طی دوره فروردین ۱۳۹۱ تا اسفند ۱۴۰۳ پرداخته شده است. یافته‌ها نشان می‌دهد ساختار انتقال قیمتی در ایران پویا، نامتقارن و شبکه‌ای است. شاخص اتصال کل مشترک (jTCI) در اغلب مقاطع، بالاتر از ۶۰ درصد قرار دارد و در دوره‌های بروز بحران‌های ارزی یا تکانه‌های سیاسی، افزایش محسوسی داشته است. تحلیل شاخص‌های جهت‌دار نیز بیانگر آن است که برخلاف انتظار، استان‌هایی با وزن اقتصادی بالا نظیر تهران، فارس و آذربایجان شرقی عمدتاً در جایگاه دریافت‌کننده تکانه‌های قیمتی قرار گرفته‌اند؛ در حالی‌که استان‌هایی چون کردستان، هرمزگان و کرمانشاه به‌عنوان فرستنده‌های اصلی تکانه‌های تورمی شناسایی شده‌اند. با این حال، باید تأکید کرد که این نتایج صرفاً به وابستگی آماری اشاره دارند. این الگو با نتایج مطالعاتی در کشورهای در حال توسعه نظیر روسیه، شیلی و نیجریه هم‌راستا است که نشان داده‌اند ساختار فضایی، زیرساخت‌های توزیع و موقعیت جغرافیایی، بیش از اندازه اقتصاد منطقه‌ای، در شدت سرایت قیمتی مؤثرند. بر اساس این یافته‌ها، توصیه می‌شود سیاست‌گذاران، در طراحی سیاست‌های ضدتورمی از رویکردی منطقه‌محور بهره گیرند و استان‌هایی با نقش سرایتی بالا را به‌عنوان نقاط هدف در مداخلات قیمتی و تنظیم‌گری شناسایی و اولویت‌بندی کنند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Regional Dynamics of Inflation in Iran: Price Spillover Patterns and the Role of Provinces in Shock Transmission

نویسندگان [English]

  • Roozbeh Balounejad Nouri
  • Mozhgan Rafat Milani
Department of Economics, Economic Affaires Research Institute, Tehran, Iran.
چکیده [English]

This study employs the Extended Joint Connectedness Approach, which integrates the Time-Varying Parameter Vector Autoregressive (TVP-VAR) model, the Generalized Forecast Error Variance Decomposition (GFEVD), and joint normalization, to investigate inflation spillovers among Iranian provinces. The dataset consists of monthly Consumer Price Index (CPI) figures for 31 provinces from April 2012 to March 2025. The findings reveal that the structure of price transmission in Iran is dynamic, asymmetric, and network-based. The Joint Total Connectedness Index (jTCI) generally exceeds 60%, with noticeable spikes during episodes of currency crises or political shocks. Directional connectedness indicators also show that, contrary to expectations, provinces with greater economic weight such as Tehran, Fars, and East Azerbaijan—tend to act primarily as receivers of price shocks, while Kurdistan, Hormozgan, and Kermanshah emerge as key transmitters of inflationary disturbances. However, it must be emphasized that these findings reflect statistical dependence and do not imply theoretical causality. This pattern aligns with studies from other developing countries, such as Russia, Chile, and Nigeria, which highlight that spatial structure, distribution infrastructure, and geographical position influence price spillovers more significantly than the sheer size of regional economies. Based on these results, it is recommended that policymakers adopt a region-oriented approach in anti-inflation strategies and identify provinces with high spillover roles as priority targets for price interventions and regulatory oversight.

کلیدواژه‌ها [English]

  • regional inflation
  • price spillovers
  • inflation connectedness
  • TVP-VAR model
  • extended joint connectedness
کهریزی، مراسلی، عسگری، حشمت اله. (2018). پویایی های تورم استان های ایران: رویکرد اقتصادسنجی فضایی. پژوهش‌های اقتصادی ایران، 23(77)، 139-167.‎
Abbas, S. J., & Arshed, N. (2023). Examining Determinants of Regional Inflation Heterogeneity, A Robust Panel Data Analysis, SAGE Open, 13(4), 1-25. Retrieved from https://journals.sagepub.com/doi/10.1177/21582440231217848.
Antonakakis, N. (2023). Measuring spillover effects in economic networks: New directions and policy implications. Journal of Economic Surveys, 37(2), 345–372. Retrieved from https://doi.org/10.1016/j.pacfin.2021.101539.
Alizadeh, Sh., Eivazlou, H., & Matlabi, M. (2021). A spatial analysis of the effect of inflation and unemployment on poverty in Iranian provinces. Journal of Computational Economics, 1(1). [in Persian].
Al-Nassar, N. S. (2023). Inflation Spillovers among Advanced and Emerging Economies: Evidence from the G20 Group. Economies. Economies, 11(4), 126. Retrieved from https://doi.org/10.3390/economies11040126.
Acemoglu, D., Carvalho, V. M., Ozdaglar, A., & Tahbaz‐Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80(5), 1977–2016. Retrieved from https://doi.org/10.3982/ECTA9623.
Antonakakis, N., Chatziantoniou, I., & Filis, G. (2017). Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest. International Review of Financial Analysis, 72, 1-26. Retrieved from https://doi.org/10.1016/j.irfa.2017.01.004.
Abounouri, E., & Rouzitalab, A. (2025). The effect of inflation and unemployment on multidimensional inequality in Iranian provinces: A spatial econometrics approach. Quarterly Journal of Economic Research (Growth and Sustainable Development), 25(2). Retrieved from https://doi.org/10.48311/ecor.2025.13662 [in Persian].
Balcilar, M., Bekiros, S., & Umar, Z. (2021). A new approach to measure connectedness of economic variables: Joint connectedness index. Resources Policy, 94, 351–364. Retrieved from https://doi.org/10.1016/j.resourpol.2021.102219.
Beck, G. W., Hubrich, K., Marcellino, M., & Adam, K. (2009). Regional inflation dynamics within and across euro area countries and a comparison with the United States [with discussion]. Economic Policy, 24(57), 141–184. Retrieved from https://doi.org/10.1111/j.1468-0327.2009.00215.x.
Çakır, M. (2023). Regional inflation spillovers in Turkey. Economic Change and Restructuring, 56(2), 959–980. Retrieved from http://link.springer.com/10.1007/s10644-022-09455-8.
Crozet, M., & Soubeyran, P. K. (2004). EU enlargement and the internal geography of countries. Journal of Comparative Economics, 32(2), 265-279. Retrieved from https://doi.org/10.1016/j.jce.2004.02.009.
Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. Retrieved from https://doi.org/10.1016/j.ijforecast.2011.02.006 .
Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. Retrieved from https://doi.org/10.1016/j.jeconom.2014.04.012.
Jiang, Y., Qu, B., Hong, Y., & Xiao, X. (2024). Dynamic connectedness of inflation around the world: A time-varying approach from G7 and E7 countries. Quarterly Review of Economics and Finance, 95, 111-125. Retrieved from https://doi.org/10.1016/j.qref.2024.03.006.
Kia, A., & Jafari, M. (2020). Forward-looking agents and inflation in an oil-producing country: Evidence from Iran. Asian Economic Journal, 69(C), 1-15. Retrieved from https://doi.org/10.1016/j.asieco.2020.101217.
Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. Retrieved from https://doi.org/10.1016/0304-4076(95)01753-4.
Karami, Kh., & Khanzadi, A. (2023). The impact of development opportunity distribution on inflation persistence in Iranian provinces. Economic Policies and Research, 2(4), 70–100. Retrieved from https://doi.org/10.22034/jepr.2024.140994.1106 [in Persian].
Hemmati, A., Niakan, L., & Varahrami, V. (2018). The External Determinants of Inflation: The Case of Iran. Iranian Economic Review, 22(4), 741–752. Retrieved from https://ier.ut.ac.ir/article_66641.html.
Lastrapes, W. D., & Wiesen, T. F. (2021). The joint spillover index. Journal of Economic Modelling, 94, 689-689. Retrieved from https://doi.org/10.1016/j.econmod.2020.02.010.
Marques, H., Pino, G., Dios, J. D., & Tena, H. (2014). Regional Inflation Dynamics Using Space-Time Models. Empirical Economics, 47(3), 1147-1172. Retrieved from https://link.springer.com/article/10.1007/s00181-013-0763-9.
Martincus, C. V. (2010). Spatial effects of trade policy: Evidence from Brazil. Journal of Regional Science, 50(2), 541-569. Retrieved from https://doi.org/10.1111/j.1467-9787.2009.00617.x.
Martin, P., & Ottaviano, G. I. P. (2001). Growth and agglomeration. International Economic Review, 42(4), 947–968. Retrieved from https://www.jstor.org/stable/826980.
Mehrara, M., & Sujoudi, A. (2015). The Relationship between Money, Government Spending and Inflation in the Iranian Economy. International Letters of Social and Humanistic Sciences, 51, 89–94. Retrieved from 10.18052/www.scipress.com/ILSHS.51.89.
Nwosu, C., & Akpan, U. (2024). Monetary Policy, Sub-National Inflation Dynamics and Regional Spillovers in Nigeria. Journal of Social Sciences, 19(1), 28–44. Retrieved from https://doi.org/10.3844/jssp.2024.28.44 .
Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29.  Retrieved from https://doi.org/10.1016/S0165-1765(97)00214-0.
Pham, B. T., & Sala, H. (2022). Cross-country connectedness in inflation and unemployment: Measurement and macroeconomic consequences. Empirical Economics, 62(3), 1123–1146. Retrieved from https://link.springer.com/article/10.1007/s00181-021-02052-0.
Tiwari, A. K., Shahbaz, M., & Islam, F. (2015). Does financial globalization stimulate economic growth? The roles of reforms and institutions. Economic Modelling, 49, 648–661. Retrieved from 10.1016/j.ribaf.2020.101247.
Tiwari, A. K., Bhanja, N., & Dar, A. B. (2016). Frequency based co-movement of inflation in selected euro area countries. OECD Journal: Journal of Business Cycle Measurement and Analysis, 2, 1–13. Retrieved from 10.1787/jbcma-2015-5jm26ttlxdd1.
Wilkinson, G. (2011). The Behaviour of Consumer Prices Across Provinces. Bank of Canada Discussion Paper, 2011-2. Retrieved from https://doi.org/10.34989/sdp-2011-2.
Widiarsih, D., Taifur, W. D., Ridwan, E., & Devianto, D. (2024). Inflation Connectedness Network in Indonesia. Inflation International Journal of Economics and Finance Studies, 15(04), 391-417. Retrieved from https://doi.org/10.34109/ijefs.202315419.
Younesi, A., Farhang, A., & Nikpey-Pessian, V. (2024). The impact of inflation on unemployment in Iranian provinces: A spatial econometrics approach. Iranian Journal of Applied Economic Studies, 13(49).  Retrieved from https://doi.org/10.22084/aes.2023.27865.3594 [in Persian].