Economic Development
mohaddaseh soleimani; Aliasghar Banouei; Esfandiar Jahangard; teymor mohamadi
Abstract
Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by ...
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Innovation and technological changes spans various geographical locations over the time.The inability of Input-Output models in measuring the effects of technology changes, caused by new innovations, is known as a weakness of these models. In this article, we show how this weakness can be addressed by employing the fields of influence method. Technology changes are modeled as changes of one or more elements in the direct coefficients matrix and the impact of such changes in the Leontief matrix is measured. Here is the main question: Does the technology changes only impact a limited sector or the entire economical system? In other words, how would technology changes in one sector impact other sectors of economic system? The main goal in this paper is proposing a method which can measure how different sectors get impacted by changes at different levels such as one element, all elements, one row or one column and then evaluates the importance of different sectors. To this aim, Iran’s Input-Output tables over the period of 1365-1395 with the fixed price of Iran’s statistics center in 1390 is used. The impact of technology changes on each sector is measured using Leontief’s inverse matrix and the column field of influence approach (CFOI) approach. Our findings indicate that over this period of time, technological changes in the industry and then construction sectors have the most influence and the mining sector has the least influence on other sectors of Iran’s economy.
Ali Asghar Banouei; Behzad Almasi Koupaie; Azita Jahani; Mehri Ameri; Mahya Lali; Saeedeh Saadatmandi
Abstract
In the combined domain of economy and environment, the process of production of goods and services contain three intertwined cycles: primary cycle (natural resources), secondary cycle (intermediate and final goods and services) and the end cycle (overflows, wastes or waste disposal to the environment). ...
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In the combined domain of economy and environment, the process of production of goods and services contain three intertwined cycles: primary cycle (natural resources), secondary cycle (intermediate and final goods and services) and the end cycle (overflows, wastes or waste disposal to the environment). The Monetary Input - Output Table (MIOT) organizes only the visible production process of goods and services and data are in terms of price - quantity simultaneously. Prices in MIOT are ordinary, homogeneous and positive for an accounting period. The other two cycles are exogenous with zero prices. As they are outside of the accounting system, we call them invisible cycles. In order to remove this limitation, the Physical Input - Output Table (PIOT) has been designed by some of European countries at the end of 20th Century. This table considers simultaneously all the three cycles in the visible manner. The data are of physical in nature (in tons) without prices and mass unit instead of value unit is used. The design of the PIOT parallel to the MIOT is triggered by two major questions among the analysts in the 21th Century. Firstly, which one of the two tables can reveal the interworen physical nature of economic-environment and sustainable development? Secondly, analogous to the basic theory of MIOT, is it possible to model the PIOT? With respect to the questions posed, the existing literature in the past fifteen years are classified into three groups: The empirical evidences of the first group show that as compared to the MIOT, the PIOT has more potentiality in revealing the physical nature of the combined economic-environment in relation to the sustainable development. This finding is questioned by the second group. The third group has cast doubts to the pros and cons of the treatment of waste as input or output and suggest that the differences are not in the treatment of waste as an input or output. According to them, the root of the differences lies in the nature and the function of prices in both the MIOT and PIOT. The third group overshadows two points: One is that they have not identified the use of the different types of prices like; implicit, unit and homogeneous or implicit matrix prices in converting PIOT to MIOT. Second is that they have not discussed the issue of the balancing of the converted PIOT to MIOT. Based on the 1990 PIOT and MIOT of Germany, we demonstrate first of all that the double deflation method cannot convert the PIOT into MIOT and secondly, use of the implicit matrix price under the assumption of the zero price of waste can convert the PIOT into the MIOT.
Ali Asghar Banooi; Mohammad Jolodari Mamaghani; Seyed Iman Azad
Volume 13, Issue 41 , February 2010, , Pages 53-77
Abstract
Using Conventional methods of Chenery-Watanabe and Rasmussen in inter industry linkages hae three limitations: Supply and demand sectors cannot be distinguished, distinction between balanced and unbalanced growth strategies are not clear and the measurement of inter industry linkages mainly depends on ...
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Using Conventional methods of Chenery-Watanabe and Rasmussen in inter industry linkages hae three limitations: Supply and demand sectors cannot be distinguished, distinction between balanced and unbalanced growth strategies are not clear and the measurement of inter industry linkages mainly depends on the size of sectoral intermediate demands. In this paper, we introduce an eigenvector method to overcome those limitations. We use the 22 aggregated sectors of the 1380 (2000) survey-based Input-Output table. The overall results show high correlation coefficients between the conventional methods. Furthermore,, we find that the eigenvector method is able to better identify those sectors which remains in the production process and therefore the key sectors.
Fatemeh Bazzazan; Ali Asghar Banooi; Mahdi Karami
Volume 13, Issue 39 , July 2009, , Pages 29-52
Abstract
The importance of spatial economy has been considered recently in Iran and has been investigated in the form of single regional input-output model in a series of articles which is a mutation in the regional studies in Iran. In these studies regional coefficients were calculated and tested statistically. ...
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The importance of spatial economy has been considered recently in Iran and has been investigated in the form of single regional input-output model in a series of articles which is a mutation in the regional studies in Iran. In these studies regional coefficients were calculated and tested statistically. As applications of single regional coefficients have some limitations, overcoming to limitations, inter-regional input-output model has been developed. The main aim of this paper is to introduce a non-survey technique to estimate interregional input-output coefficients for two regions: Tehran and the Rest of Iran which is the first experience in Iran. These coefficients will enable policy makers to capture feedback and spillover effects that are primarily attribute to inter-regional trading model. In this study, regional coefficients are estimated for 10 sectors in 2001. Results show 58% of Tehran import is from the rest of Economy whereas 41% of the Rest of Economy is from Tehran. Other results also show spillover effects in Tehran province are greater than the Rest of Economy. While, small feedback effects are observed in both regions. Moreover, we found the errors of using single input-output coefficients and neglecting the spillover and feedback effects are 20% and 12% for the Rest of Economy and Tehran province respectively, both are considerable and reveals the importance of using two-region input-output model.
