Economics examines the optimal allocation of scarce resources in the face of unlimited demands. This requires access to reliable and relevant information to support effective prioritization. In the development literature, particular emphasis is placed on the capacity and relative position of regions within the national production system, as these factors constitute pillars of balanced development. The present study aimed to rank Iranian provinces and counties based on their shares in value added. Adopting a descriptive–analytical approach, the research selected the statistical population comprising 457 counties of the country for the period 2017–2020 (corresponding to 1396–1399 in the solar Hijri calendar). Given the comprehensive scope of the study, no sampling was undertaken, and the analysis was conducted using a census method. The VIKOR multi-criteria decision-making technique was applied, and Shannon entropy was employed to determine criterion weights. The input variable was each county’s share of value added relative to the national total in the corresponding sector. The data was obtained from statistical tables (published by the Statistical Center of Iran) and regional accounts. The results indicated that Tehran, Rey, and Mashhad counties achieved the highest rankings in both years, whereas Margoun, Karkheh, and Angut ranked the lowest. Provinces were also ranked using both direct and indirect approaches. Under the direct method, Tehran, Khuzestan, and Bushehr ranked highest, while Ilam, Chaharmahal-and-Bakhtiari, and North Khorasan were positioned at the lower end of the ranking. In the indirect method, Qom, Tehran, and Bushehr occupied the top positions, whereas Chaharmahal-and-Bakhtiari, South Khorasan, and Sistan-and-Baluchestan ranked lowest. Overall, the findings revealed a significant concentration of production in a limited number of regions, highlighting the necessity of targeted regional policies to promote balanced development. The results can provide valuable guidance for policymakers in designing resource allocation strategies and regional economic planning initiatives.

Introduction

Under current national economic conditions, there is broad consensus—particularly among economists, experts, and policymakers—that Iran’s level of economic growth and production does not align with the capacity of its human and natural resources. A substantial portion of economic potential remains underutilized, leading to high unemployment of resources—especially labor—and an excessive reliance of national economic growth on oil revenues, which are inherently volatile. This dependence has contributed to instability in economic planning and key macroeconomic variables. These factors have reduced overall productivity in the national economy, thus highlighting an urgent need for structural reforms aimed at the more efficient utilization of economic resources and potential.
An examination of Iran’s regional economy reveals significant disparities in performance, with some regions achieving higher-than-average levels of economic growth. Owing to differences in regional potential, levels of development across provinces are uneven in the industrial, agricultural, and service sectors. Failure to adequately recognize and utilize regional capacities leads to misaligned investments and the persistence of underdevelopment, despite the implementation of numerous national and regional development programs. These programs have largely been unable to reduce economic, social, and spatial inequalities. As a result, severe poverty in certain regions, unequal employment opportunities, uneven access to facilities, and migration continue to pose major development challenges.
Identifying the factors that influence regional economic growth enables more informed policymaking at both the national and local levels. In light of the long-term objectives set out in the Twenty-Year Vision Document—particularly the goal of attaining a leading economic position in the region—continuous monitoring of economic indicators is essential. One of the most important indicators in this regard is sectoral value added at the provincial level. However, the absence of county-level accounts represents a significant informational gap. The current study sought to address this gap by ranking provinces and counties according to their shares of value added across different economic sectors, using constant prices to eliminate the effects of inflation. The study tried to answer the following research questions: How does each province and county in Iran rank in terms of their share of value added across different economic sectors? And what is the difference between a province’s direct ranking and its indirect ranking (calculated based on the average rank of its counties)?

Materials and Methods

As a quantitative research based a descriptive–analytical approach, the present study relied on library-based documentary analysis and field survey data. Value-added indicators for 18 economic subsectors, classified according to ISIC Rev.4, were calculated at the county level. They were weighted using Shannon entropy, and ranked using the VIKOR method. The data was sourced from official national, provincial, and county-level accounts published by the Statistical Center of Iran, ensuring full consistency across spatial levels. The VIKOR method, grounded in multi-criteria optimization, was chosen for its ability to rank alternatives under conflicting criteria based on their proximity to the ideal solution.

Results and Discussion

Table 1. Comparison of Direct and Indirect Rankings of Provinces in 2019




No.


Province


Direct rank


Indirect rank


Rank difference




1


East Azerbaijan


7


16


−9




2


West Azerbaijan


9


11


−2




3


Ardabil


25


25


0




4


Isfahan


4


9


−5




5


Alborz


14


6


8




6


Ilam


29


29


0




7


Bushehr


3


3


0




8


Tehran


1


2


−1




9


Chaharmahal and Bakhtiari


30


28


2




10


South Khorasan


28


30


−2




11


Razavi Khorasan


5


24


−19




12


North Khorasan


31


26


5




13


Khuzestan


2


5


−3




14


Zanjan


26


15


11




15


Semnan


27


17


10




16


Sistan and Baluchestan


16


31


−15




17


Fars


6


19


−13




18


Qazvin


12


4


8




19


Qom


22


1


21




20


Kurdistan


23


13


10




21


Kerman


10


21


−11




22


Kohgiluyeh and Boyer-Ahmad


15


23


−8




23


Kermanshah


24


27


−3




24


Golestan


20


20


0




25


Gilan


11


12


−1




26


Lorestan


21


14


7




27


Mazandaran


8


7


1




28


Markazi


17


18


−1




29


Hormozgan


13


22


−9




30


Hamedan


19


10


9




31


Yazd


18


8


10




Source: Results Research
By utilizing newly released county accounts (published in 2021) and analyzing 457 counties over multiple years, this study addressed a significant gap in subprovincial economic analysis in Iran. The results indicated that from 2017 to 2020, the counties of Tehran, Rey, and Mashhad consistently ranked first to third nationwide. In 2020, their VIKOR index values were 0, 0.8817, and 0.8877, respectively, reflecting a strong proximity to the ideal solution. In contrast, Margun (Kohgiluyeh and Boyer-Ahmad Province), Karkheh (Khuzestan Province), and Angut (Ardabil Province) were ranked the lowest, with VIKOR values approaching one.
A notable finding is the pronounced spatial concentration of value added. Among the top 25 ranking positions during the period, 16 were occupied by counties in Tehran Province, underscoring the heavy concentration of economic activity in the capital region. Furthermore, Pearson correlation coefficients between the VIKOR index and population or land area were relatively weak. The strongest correlation (–0.152) was observed with urban population, which exerted roughly twice the influence of rural population.




Figure 1. Map of Indirect Ranking of Provinces in 2010
 


Figure 2. Map of Direct Ranking of Provinces Using the VIKOR Method in 2010
 
 




Source: Results Research
Sectoral analysis showed that in 2020, more than half of the national value added was generated by mining, real estate, industry, and wholesale and retail trade. Tehran County alone contributed over 16 percent of the national value added and dominated knowledge-intensive services, including information and communication, financial and insurance activities, and professional and scientific services. This structure differs markedly from the national pattern, reflecting the concentration of financial and technological infrastructure in the capital.

Conclusion

Iran’s development policies are largely centralized, resulting in unequal wealth distribution, rural-to-urban migration, rising unemployment, and the decline of local economic activities. The growing gap between major metropolitan areas—such as Tehran, Isfahan, Mashhad, and Shiraz—and other provincial centers highlights the urgent need for place-based regional policies tailored to local economic structures and capacities to promote more balanced and sustainable development.