Mohammad Mahdi Ahmadian Divkoti; HasanAli Aghajani; Meysam Shirkhodaei; Amir Mansour Tehranchian
Abstract
Extended abstract
1- Introduction
As stated by theoreticians, no factor can replace knowledge in the present-day economy; so that other production factors (such as labor and capital), which have been among the main contributing factors of development for decades, are also affected by such phenomenon. ...
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Extended abstract
1- Introduction
As stated by theoreticians, no factor can replace knowledge in the present-day economy; so that other production factors (such as labor and capital), which have been among the main contributing factors of development for decades, are also affected by such phenomenon. Accordingly, in the age of knowledge-based economics, many countries are seeking to develop their wealth creation through knowledge; thus, they seek to organize a mechanism in which knowledge is created based on the needs of society, which helps them pass through the path to maturity and evolution, and ultimately leads them to the wealth creation (Hasani, Rafiei & Bakhshiani, 2016).To measure the level of knowledge used in a country’s products, there are several indicators one of which is the economic complexity index (Pazham & Salimifar, 2016) proposed by Hidalgo and Hausmann (2009); to measure the complexity of the countries’ economy (Hidalgo & Hausmann, 2009). The economic complexity approach can be used as a benchmark for assessing the effectiveness of the countries’ national innovation systems. Many models have been introduced to assess and measure the success of innovation systems, but a more complex and more realistic approach to this measure can be demonstrated in the international arena. Thus, in this article; we first provided a very brief reference to the national innovation systems of the selected countries (including Japan, South Korea, Singapore, Malaysia, and Iran), then by introducing how to calculate economic complexity, opportunity gain and distance, we compared the comparative position of these countries while encountering economic complexity.
2- Theoretical Framework
Complex economies are economies bringing together a large amount of related knowledge in the form of large networks of people and produce a diverse range of knowledge-based products. In contrast, simple economies have a poor sponsorship and support of productive knowledge and produce less and simpler goods that require a smaller network of interactions (Hidalgo & Hausmann, 2009). For this reason, the design of the national innovation system is very important in order to provide an appropriate climate in which economic agents can innovate and create technology (Weng et al., 2012). Countries that have managed to bring together components in a product have accelerated the growth of innovation and, the economic growth, consequently whereas countries with a disparate national innovation system have failed to achieve such growth (Nasiriaghdam, Dehghan Tarzjani, Rezaei & Beik Mohamadlo, 2011). As a result, the national innovation system is a necessary, effective, and dynamic factor for the development of countries (Iqbal, Khan, Bashir, & Senin, 2015).
3- Methodology
To conduct the study, the data collection was done in two stages. In the first stage, using the documentary method and the search of relevant internal and external sources, books, scientific and research publications, theoretical foundations related to the innovation system of the selected countries were studied. In the next step, since one of the indicators of the success of innovation systems is the use of knowledge and innovation in the knowledge-based products production and export, the economic complexity index is used to compare the efficiency of these systems in the global arena. If we accept that the construction of a commodity requires a specific type and composition of applied knowledge, it is obvious that a country can produce a product which has access to this applied knowledge. From this simple principle, two useful tips for constructing the economic complexity index can be derived:
1- Countries with more applied knowledge will be able to produce a more diverse range of goods. In other words, the amount of applied knowledge accumulated in a country is expressed on the basis of the "diversity" of its products, or the number of distinctive goods it produces.
2- The production of goods that require a large amount of knowledge is possible only in a limited number of countries, in fact, the countries that have all the necessary applied knowledge. (Cheshomi & Malekalsadati, 2014).
In addition to calculating the economic complexity of countries, this approach can be used to calculate opportunities for countries to diversify exports, and the distance or ability to enter a specific product; these data and information about different countries in terms of economic complexity are accessible to everyone at Harvard Business Complex Atlas Site (visit http://atlas.cid.harvard.edu). Data on the economic complexity of selected countries in this research have also been extracted from this site.
4- Findings
Examining some of the indicators of the national system of innovation model in selected countries, such as the cooperation of industrial enterprises, the interaction of industry and university as well as; technology distribution and staff turnover, shows that selected countries other than Iran have taken effective measures to strengthen their national innovation system. According to the research findings, if we look at the situation of the "product space" of the selected countries over the past decades, we will notice a very delicate point, which is a significant shift taken place in the export situation of these countries over time; and have changed from export of products with low complexity (agricultural products, minerals, raw materials, etc.) towards highly complex products (single, industrial products); however, the product space for Iran was not so. In addition, by observing the export status of these selected countries from 2000 to 2016, it was observed that; over the years; the largest share of exports has been made in Japan, Korea, Singapore and Malaysia for the products belonging to the group of machinery, electronics and chemicals which are the most complicated. However for Iran; the opposite is true, and crude oil has the largest share in Iran's export, which, has a very low value in terms of complexity. On the other hand, Iran, has a higher possibility than the other countries in terms of obtaining the opportunity, while these opportunities are far away from the country’ reach, that is, the country's capabilities to achieve these opportunities must be strengthened. Concerning the points of interest for the selected countries, it is true that they have a lower rating in terms of opportunity, but these opportunities are closer to them. The next point is that for the selected countries, the high-tech products are closer in terms of distance; and because of the lack of adequate natural resources; or the implementation of rigorous policies in exploiting these resources, the raw materials, mineral resources and agriculture are far away. For Iran, the situation is a little different; raw materials, minerals, and crude oil, are closer for exploitation, and high-tech products are far from Iran in terms of distance although being less attractive for the benefit of the opportunity.
5- Conclusion
Economic complexity requires the policy makers to change attitudes in various fields, and the creation of synergy and coordination among all policies, so as to distance themselves from simple and linear causal relationships. They should also emphasize the promotion of the technological and innovative capabilities needed to sustain the country's sustainable development. This implies the need for a duplicate effort in the transition from a resource-based economy to a knowledge-based economy. It also requires the integration of the innovation policy into the package of the country's development policy, which should be pursued seriously by the central institutions in the public and private sectors. Changing the key variables of the economy is not achieved simply by changing price or encouraging the tax or establishing a law or establishing an organization or institution. It also requires special attention to the national system of innovation and the creation of coordination and synergy among all actors and institutions involved in this system. Of course, to accelerate the realization of economic complexity, the policies and experiences of the leading countries in the field of the national system of dynamic innovation can be used while taking into account the position, capacity, and potential of the country.
seyed mahdi pazham; Mostafa Salimifar
Abstract
Extended Abstract
Introduction
Economic growth and development has always been being a major goal of policy makers. They have always been seeking factors to increase growth's speed. There are some different theories that each one, account of some kinds of factors related to the growth. In the earlier ...
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Extended Abstract
Introduction
Economic growth and development has always been being a major goal of policy makers. They have always been seeking factors to increase growth's speed. There are some different theories that each one, account of some kinds of factors related to the growth. In the earlier of growth literature theories, the focus was on two factors: physical capital and labor. But these theories couldn't exactly explain the persist gap between different countries ‘per capita income. This cause to more pay attentions to some other factors that are seemingly insensible in the first glance. The advent of knowledge- oriented economics is the outcome of this new vision on growth field. In modern economics, knowledge is the main factor in production function. There are some indicators to measure the knowledge applied in a country's products. Economic complexity index is one of them. This article wants to examine the effect of this variable on economic growth. For this, the article examine growth model by using panel econometrics technique during 1996-2012 for 42 Chosen Countries (The top 42 countries producing science).
The structure of this paper, in theoretical basis, is to examine the ideas of economists in the world and background research, furthermore, Economic Complexity Index and check out selected countries in this indicator, research and study models will be introduced. Final section will be devoted to analyzing the results and conclusions estimates.
Theoretical Frame Work
As seen in all of these theories, knowledge has always been considered the engine of economic growth in two ways on the production and consequently affects economic growth: as a new production or to increase the overall productivity of production factors.
Since 2006, a group of authors began to explore the extensive economic growth based on the idea of "the products" and "complexity economics" were. The group's research led to the extraction of economic complexity Index (Hidalgo and other, 2007). Based on this thinking, the most important determinant of the level of development of each country, based on its knowledge of the country. Knowledge means of a stream of experiences, values, and attitudes expert information system is a framework to evaluate and take advantage of the experience and new information gives (APEC.2002).
Methodology
In this study, data from the first 42 countries in the production of knowledge is analyzed. Period of study 2012-1996 Ast years. Statistics variables above except the index of economic complexity, for all the countries in the study were collected from the site of the World Bank. In order to avoid bias said, be on the side of the complexities of economic and other factors affecting economic growth are properly specified model.
According to the theoretical literature on the factors affecting economic growth, the most important variables affecting economic growth in the countries studied, per capita physical capital formation (CF), government size (GE), human capital (LE), the volume of trade (TRAD), in addition to the economic complexity index (ECI) growth models have been added.
Econometric research process consists of three steps:
1. Cross-sectional data unit root test
2. The accumulation of data on cross-examination, if not stationary variables
In the case of co-integration vector accumulation estimate coefficients of the variables
Results and Discussion
As mentioned, according to the estimated model, the relationship between economic growth and negative economic complexity index, and this is unexpected. To investigate the cause of the issue, again a model for cross cutting (Cross-Section) estimated that the estimated model, the relationship between these two variables is positive and significant for the years after 2006. For a certain period and between different countries is presented. The results show using panel data technique is not appropriate, however cross-section estimation of model shows positive effect of Economic complexity index on economic growth.
Conclusions & Suggestions
In advanced economies contemporary knowledge in the development and growth of the country's annual production (GDP), played a key role stems. Economic Complexity Index, an indicator for measuring the amount of product used in a country. In this study, the relationship between these indicators and economic growth top 42 countries in the production of a 17-year period (2012-1996) and related techniques using panel data consists of panel unit root, panel Hm Anbashtgy , Has been studied. The results of research panel data; on the contrary the index suggests a negative relationship with economic growth of the countries that represent the inappropriate use of panel data in this research model. But the results of cross-sectional data model represents a significant and positive relationship between these variables on economic growth.
Economy reaching a middle-income country in the world, due to the unlimited supply of natural production factors (eg oil and abundant labor force) and rely on a certain level of production and industries heavily on its user.
