Document Type : Research Paper

Authors

• Mahya Allahgholi ¹
• Farshad Momeni ²

¹ Ph.D. Candidate in Economics, Allameh Tabataba’i University, Tehran, Iran

² Professor in Economics, Allameh Tabataba’i University, Tehran, Iran

Abstract

The Economic Complexity Index (ECI) can be considered as a development indicator, given its superior predictive power in predicting economic growth and income inequality. However, it suffers from shortcomings such as the inability to distinguish differences in the complexity levels of economies. This highlights the need for a theoretical model to explain the ECI. Within the framework of the social orders approach, the type of social order is identified as a key distinction between developed and developing economies. Using a descriptive–analytical method, this study aimed to identify the influential factors of the ECI. In this respect, three key variables were examined: the state of property rights, the business environment, and the type of people’s access to organizations. The analysis focused on Iran’s ECI over a ten-year period (2010–2020), alongside three other indices, namely International Property Rights, Ease of Doing Business, and Economic Freedom— as an estimates of the chosen variables. According to the results, the International Property Rights Index, compared to the other two indices, has the strongest positive correlation with the ECI.

Introduction

Assuming stable conditions, the Economic Complexity Index (ECI) measures a country’s production capacity and its potential future development by analyzing the information about its exports. Countries that produce and export more diverse and unique products tend to have more complex economies, leading to higher economic growth prospects and reduced inequality. Such countries manage to produce better and smarter products by sharing knowledge among citizens and reintegrateing knowledge within institutions, organizations, and groups. However, the ECI does not explain why some economies become more complex over time while others do not. Understanding these dynamics requires more in-depth studies of various economic conditions and factors influencing the ECI. Using the social order approach as an analytical framework, the present research aimed to explore why Iran’s economy has failed to improve in the ECI rankings over recent years. A key determinant of economic complexity is productive knowledge. This kind of knowledge manifests in the variety of existing companies, the range of jobs required to sustain them, and the level of interaction between companies within the society. Therefore, understanding differences in the levels of economic complexity and their future trajectories depends on how effectively these economies expand the total pool of knowledge, as in increasing the diversity of knowledge available to people and enterprises and fostering conditions that enable its integration through organizations, which serve as human interaction networks.
In their analysis of social orders vis-à-vis violence control, North et al. (2009) categorized countries into two types: limited access (natural states) and open access. The key distinguishing factor of an open access order is the presence of competition at all economic and political levels. Based on this approach, three levels of explanation can be proposed to account for differences in economic complexity and the processes these countries undergo. The first level concerns the type of people’s access to organizations. In an open access order, this access provides opportunities for economic entrepreneurs to engage in creative destruction. Within this structure, entrepreneurs can advance toward more complex products by modifying existing production processes or developing new products through investment in human capital and the accumulation of physical capital by shifting the boundaries of existing knowledge. The second level focuses on the business environment, which influences the motivations of individuals and companies. The business environment within a society is considered as a key factor shaping individual and corporate choices to diversify knowledge and learning. Finally, the third level addresses transaction costs associated with integrating knowledge within organizations. Given that transaction costs and property rights are measured by similar criteria, the third key factor influencing economic complexity is the state of property rights.

Materials and Methods

The theoretical–conceptual model illustrating the relationship between three factors influencing economic complexity is shown in Figure 1. To assess the type of people’s access to organizations, the business environment, and property rights, the following indices were used: the Economic Freedom Index from the Heritage Foundation, the Ease of Doing Business Index from the World Bank, and the International Property Rights Index. The research adopted a descriptive–analytical method and conducted data mining using Power BI and Excel. It is important to note that some data on sub-indices for Iran are incomplete or inaccurately estimated. Consequently, using them in a model to study Iran’s economy may lead to errors. Therefore, this study is limited to analyzing existing trends.
Figure 1. The theoretical–conceptual model of the relationship between property rights, business environment and people’s access to organizations with economic complexity
 
Source: Research findings

Results and Discussion

According to the Atlas of Economic Complexity, in 2020, Iran ranked 85th out of 133 countries, with an economic complexity index of -0.39. Over the past decade, the index has shown only a slight improvement, and Iran’s ranking has risen by 11 points. Given the significant share of fuels in Iran’s exports, an analysis of this sector alongside the economic complexity index trend revealed that a decline in the fuel sector’s share generally coincided with an improvement in complexity index. However, the lack of improvement in Iran’s ECI—despite a decrease in the fuel sector’s share in 2012, 2015, and 2019—can be attributed to the addition of more low-complexity goods to the export basket during those years. Conversely, the increase in the fuel sector’s share in 2017, alongside no change in the complexity index compared to 2016, resulted from the inclusion of products with positive complexity in the export basket that year. According to the findings, the improvement in Iran’s ECI resulted from the improvements in the sub-indices of political stability, registering property, and patent protection (in the International Property Rights Index), protecting minority investors, dealing with construction permits, and getting electricity (in the Ease of Doing Business Index), as well as governance integrity and trade freedom (in the Economic Freedom Index). Additionally, the study found that the ECI has a positive and moderate correlation with the International Property Rights Index (0.49), the Ease of Doing Business Index (0.55), and the Economic Freedom Index (0.41). The correlation coefficients of these indices with Iran’s ECI were found to be 0.52, 0.21, and 0.48, respectively.

Conclusion

This study used of the social order approach as a theoretical framework, which significantly contributed to a better understanding of the factors influencing the ECI. The analysis also demonstrated that the International Property Rights Index provided a better explanation of the trend in Iran’s ECI compared to the other two indices.

Keywords

• Economic Complexity Index
• Social Orders
• Property Rights
• Business Environment
• Type of People’s Access to Organizations

Main Subjects

• Economic Development