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Development literature show that the main concern of international organizations and scholars and scientific and research centers in the third millennium is human education and scientific development as an effective factor in development. This research aims to investigate the time series of the impact of science and technology on development. The type of this longitudinal research is time series and is intended to estimate, predict the time series of the impact and the trend of science and technology on development in the period 1980-2015 in 12 selected countries. The Selected countries have been selected in a targeted way the results of data analysis with R software show that by analyzing the significant difference between countries in the variable of human resources and education and technology variables by ANOVA, Significant differences between countries are confirmed. The results of dispersion graphs in all selected countries show upward trends. In general, the results indicate that growth and development during the 1980s to 2015 is on the rise and the trend of the impact of education and technology variables on development is on the upside, too.

The role and importance of knowledge in economic growth has been considered since the second half of the twentieth century. As of 1980s, knowledge entered the production function as an endogenous and determining variable. By the time that knowledge, innovation and new technologies became of value; broad studies were carried out in order to investigate the role and impact of these variables on economic growth, both at national and regional (regions within the national borders) levels. Economic researchers have tried to explain the disparities in economic growth of regions according to the differences in knowledge share and innovation. Through the production and publication of financial accounts of provinces in Iran since 1990, the pathway for such studies has been smoothed and the ground has been prepared for investigating the role and impact of knowledge and innovation on economic growth of different provinces and their diversity in economic growth. In the present article, the effects of knowledge variables (including specialized labor, R&D employees and value-added of high-tech sectors) have been surveyed alongside with two traditional variables of labor and capital on economic growth of Iran provinces during years 1990-2011 and the economic growth model has been estimated through this approach. The results of model estimation using stochastic effects method reveal that specialized labor growth rate has the highest effect on economic growth of provinces, by a coefficient equal to 2.05. The growth rates of capital per capita, and high-tech and intermediate-tech industries (per employee) have the coefficients of 0.89 and 0.19, respectively.

This study investigates interactions between economic growth and natural gas consumption, using times series data. The paper uses vector error correction technique and Johansen Co-integration test for the period 1353-1386. Co-integration test results indicate that there are two co-integrating vectors containing GDP and natural gas consumption. In order to identify the co-integrating vectors, restrictions based on fundamentals of economic theory are imposed. Each vector can be interpreted as follows: in cointegrating equation1, gas consumption, capital, research & development and labor force variables have positive and significant effects on GDP (endogenous growth function) in the long run, based on theoretical foundations of endogenous growth function is quite plausible. In cointegrating equation 2, GDP has positive and significant effect on gas consumption in the long run. Also, there are short-term dynamics in ECM equations in which speed of adjustment coefficients are offered. The results indicate that there is bidirectional causality between gas consumption and GDP in Iranian economy. So myiopic policies on one side without considering the other side is not expected to be effective. This means that policies designed for restraining gas consumption policy, ceteris paribus, may lead to decline in GDP.

Endogenous growth model developed here emphasizes dynamics, with explicit modeling of knowledge accumulation. Considering the uncertainty inherent in any search process, the model presents a dynamic stochastic system in which new technology and capital accumulation are boundedcomplements—they complement each other to a point, but beyond this the impact of each factor is constrained by the level of the other. As a result, both technological progress and capital accumulation are necessary for sustained growth, but neither on its own is sufficient. Technological advancement stimulates capital accumulation by raising the marginal product of capital. Rapid capital accumulation stimulates R&D investments by raising the expected profitability of innovation. This paper discusses different possible regimes that an economy may find itself in as a result of the interactions between capital accumulation and technological innovations and has important implications for growth-promoting policies, knowledge spillover, and international flow of capital.

The economic growth rate is an important issue which concerns most of the economic intellectuals, because the economic Growth rate is one of the most important factors which have effect on the human Social welfare. But in spite of the importance of economic growth rate, determining different factors affecting on growth of a country still are mysterious and to some extent controversial. trade strategy, among the others, is one of the most important explanatory variables of growth. One the other hand, the effect of trade on growth is considered as one of the most important topics in growth and trade literature. From an economic point of view, The most important opinions of advantage is documented and during the evolution of advantage-based theories, The Theory of Competitive advantage and competitiveness, had introduced , Since the and of The Year 1990. We decided to examine the impact of competitiveness on economic growth. To provide a composite measure of competitiveness, caring the sources of competitiveness, we focused on the effectiveness of above mentioned measures on different elements of production function. So, we introduced three indices of labor force, capital and technology competitiveness, then we calculated these measures for 57 countries during the period of 1995-2003 and countries in to four groups based on income levels according to the world bank classification. Finally, the estimation of model would have done (by considering above measures). Three functional forms of the production function were suggested regarding the different forms of technology (labor-augmenting technological progress, capital- augmenting technological progress and Hicks-Neutral form). Then using a panel data regression model, the strong and positive relationship, had been confirmed. .