بررسی اثر تمرکز صنعتی در کارایی انرژی بخش صنعت در استان‌های ایران

Introduction: Industry is one of the sectors that plays a significant role in economic growth and, on the other hand, has high energy consumption. From the environmental point of view, high economic growth along with optimal life quality is a main objective for economy. Any disagreement among economic objectives may impose heavy costs on the economy. Development of the industry sector, due to its importance in economic growth, plays a crucial role in economic development and the level of energy consumption in that sector, which is more than that in the other sectors of the economy. In this regard, improvement of energy efficiency in the industry sector is an important policy for the reduction of negative effects of economic growth.
Methodology: To estimate the effect of industrial concentration on energy efficiency at the provincial level during 2004 to2014, the following equation was used.
 
In this equation, eff denotes the calculated efficiency of energy by Stochastic Frontier Analysis (SFA) in I provinces and t time, conc shows Alison Glassier industrial concentration index, r&d is the research and development expenses, com is the cost of communication and computer, and w is the standardized spatial matrix. To measure the efficiency of the consumed energy, SFA was used. Also, to estimate the energy efficiency from point of view of production, the Shephard Di
The Alison Glassier Index was employed to calculate the industrial concentration index (y) as follows:
 
Results and Discussion: The results obtained from the calculation of Alison Glassier Index for each province in the period of 2004-2014 shows that the highest industrial concentration of 0/593 for Booshehr and the lowest for Markazi Province which is 0/028. One of the main reasons for the high index in Booshehr is the industrial structure of this place. In fact the share of this province in the production of chemical products was 40 percent of the total products of the country in 2014.
In fact, Markazi Province has simultaneous roles in most industries and, thus, had the least industrial concentration in 2014.  The result obtained for the other provinces indicates that East Azarbayjan and Qhazwin by 0/03 are among the provinces with low industrial concentration. Ilam, Kerman, Hormozgan, Sistan and Balouchestan are among the places with high industrial concentration. Based on the data of 2014, the share of Hormozgan in the total production of the country in most industries is almost zero.
A survey of the changes in the concentration index of all the provinces shows that, on average, concentration reduced from 0/132 in 2004 to 0/115 in 2006, and then it increased to 0/191 in 2013. The results obtained by SFA also reveal that Booshehr had the highest energy efficiency of 0/93 while North Khorasan with the efficiency of 0/134 had the lowest amount of energy efficiency. The result also shows that six provinces with energy efficiency of higher than average had a concentration higher than average. Also, 11 provinces with efficiency rates lower than average had the lower-than-average industrial concentration. Therefore, in 17 provinces, the rates of efficiency and concentration were the same. In fact, the provinces with higher or lower energy efficiency were those with high or low industrial concentration. Only in 13 provinces, the rates of energy efficiency and concentration were in opposite directions. The study of the changes in the energy efficiency of all the provinces shows that, on average, the amount of efficiency increased significantly from 0/398 in 2004 to 0/525 in 2014.
The results from the estimation of SDF also show that the level of Gamma was almost zero and, thus, variation in the energy efficiency was insignificant. Energy efficiency increased from 0/4 in 2004 to 0/53 in 2014.
The analysis by the Granger causality method shows that there is a relationship between industrial concentration and energy efficiency. Its positive or negative effect on energy efficiency can be known by the other models of econometrics such as spatial econometrics.
There are three steps for the estimation by the spatial model of Elhorst used in this paper. Firstly, Moran statistics are used to investigate the existence of spatial effects in the variable of energy efficiency and the residuals of factors effecting energy efficiency. Then, by the statistics of Lagrange coefficient, all types of spatial effects (spatial errors or spatial lag) are evaluated. Thirdly, by the use of the maximum likelihood test, the fixed effects of space and time are studied, and ultimately Hassman Spatial Test reveals the type of the estimated model.
In general, to survey the effective factors in the energy efficiency of manufacturing sectors, the spatial model of econometrics is used through the method of random effect and by considering the spatial heterogeneous effects along with two spatial lags and spatial error. The result reveals that, whatever the level of industrial concentration increases, the level of energy efficiency reduces at the error level of 0/05. Thus, a one-percent increase at the level of industrial concentration will reduce the level of energy efficiency by 0/056.
Conclusion: Kaldor (1966) believes that industrial sector is the growth engine for the economic development of a country, and evidence shows that the amount of energy consumption in this sector is more than in the other sectors of the economy. Thus, the present study tries to determine the efficiency of energy consumption and the effect of concentration of industry on energy efficiency by using the data of manufacturing industries in the Iranian provinces from 2004 to 2014. The results of the estimation of the spatial econometrics model show that the effect of industrial concentration on energy efficiency is negative and statistically significant at the error level of 5%. Therefore, an increase in industrial concentration reduces the energy efficiency. In addition, the effect of research and development on energy efficiency is positive and significant, but the effect of computer and communication on energy efficiency is negative and significant. Therefore, improvement of research and development expenditure can increase energy efficiency and environment quality. Also, diversification of industrial activities in regions on the bases of their potentials can be an optimal policy to increase energy efficiency.