Ali Asghar Banou'i; zahra zabihi; parisa mohajeri; elham tabrizi
Volume 15, Issue 59 , January 2016, , Pages 95-124
Abstract
Errors which occur in the process of collecting and compiling databases and developing symmetric input-output tables are inevitable. The issue of stochastic data contained in the input-output tables has been one of the key issues discussed in input-output economic literature. Foreign researchers have ...
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Errors which occur in the process of collecting and compiling databases and developing symmetric input-output tables are inevitable. The issue of stochastic data contained in the input-output tables has been one of the key issues discussed in input-output economic literature. Foreign researchers have demonstrated in theoretical studies that if the matrix of technical coefficients is stochastic, the Leontief production multipliers will be positively biased. Although the findings of applied studies (that include the complier's and practitioner's approach) confirm the above observation, but they also show that this bias is trivial and therefore can be ignored. In this study, the approaches of practitioner and complier to the analysis and estimation of the bias of stochastic input-output multipliers and the estimation of multiplier bias are explained. For this purpose, we use Monte Carlo simulation method from the Complier’sview to estimatethe bias of production multipliers and the effect of sample size on the bias. The findings of this study suggest that, first, the greater the sample size the less the amount of bias of multipliers and second, the greater the sample size, the higher percentage of elements in matrix of production multipliers demonstrate a positive bias. Third, in a sample with large size, all multipliers have significant positive biases that is in line with the findings and results of analytical studies, however this bias is very small.
Hojjatollah Mirzayi; Ali Asghar Banou'i
Volume 15, Issue 58 , October 2015, , Pages 84-110
Abstract
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 ...
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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.