بررسی کارایی فنی و مقیاس مصرف نهاده‌های انرژی صنایع کارخانه ای استان‌های کشور پس از اجرای قانون هدفمندکردن یارانه‌ها

Extended Abstract
Purpose: Economic growth is influenced by two factors including the accumulation of production factors and the increase in efficiency. Efficiency is one of the important issues of the economy. Although its improvement is necessary for all countries, it is of double importance in developing countries, due to the lack of superior technology and more waste of resources and production inputs. Since the industry sector constitutes a high share of the gross domestic product and is of great importance due to its previous and subsequent connections with other economic sectors, the improvement of efficiency in this sector can lead to an increase in employment, production, and income in the entire economy. The industry sector is one of the significant energy-consuming sectors in every country, and the improvement of energy efficiency as one of the important policy tools plays an essential role in the growth of the industry. Therefore, this study examines the technical efficiency and scale of energy consumption of the industries in the provinces of the country. To this end, the non-parametric method of Data Envelopment Analysis (DEA) is used. Also, the issue of targeting energy subsidies in 2019 has had a significant impact on the cost of energy consumption in the industrial sector of the country. On this basis, the present study analyzes the technical efficiency of energy in the years after the implementation of this law. Considering the difference in the share of energy consumption according to the type of energy carriers at the industry level, we have considered four leading energy carriers for the calculation of efficiency.
Methodology: The research steps include defining an appropriate model for calculating technical efficiency, determining the type of DEA model in terms of input or output-oriented and the type of efficiency with regard to scale, collecting, calculating the technical efficiency and the scale of the industrial sector of each province, and finally analyzing the results. Data envelopment analysis (DEA) is a non-parametric linear programming method for evaluating the efficiency of decision-making units (DMU). The main advantage of this method compared to parametric methods such as the stochastic boundary function is that the shape of the distribution function and the production relations do not create a limit for it. In addition to technical efficiency, scale efficiency can be obtained for all units by calculating the ratio of technical efficiency in the state of constant efficiency to technical efficiency in the state of variable efficiency. The researchers used the input-oriented multi-stage DEA model with six inputs and one output to determine the technical efficiency and the energy consumption scale efficiency of the industrial sector in 31 provinces. In this model, the variables of labor force (people), formation of real fixed capital (million rials), consumption of natural gas, diesel, fuel oil and electricity (barrels equivalent of crude oil) in the industry sector of each province are the  inputs, and the actual output of the industry sector (million rials) in each province is considered as the output.
Findings and Discussion: The results of technical and scale efficiency scores of industries in the provinces analyzed with the multi-stage DEA model during the years 2011-2019 show that, in 2011 (the beginning of the subsidies targeting), only active manufacturing industries in the provinces of Isfahan, Ilam, Bushehr, Tehran, Khorasan Razavi, North Khorasan, Khuzestan, Sistan and Baluchistan, Kermanshah, Kohgiluyeh and Boyer Ahmad, Gilan, Markazi, and Hormozgan were technically efficient. The inefficiency was higher in Lorestan, Golestan, Yazd, and West Azerbaijan provinces. Also, over time, when the effect of the increase in the price of energy carriers became more evident in the subsidy targeting law, the technical efficiency was relatively improved in most of the provinces. The noteworthy point here is that, among the efficient provinces, Tehran, Bushehr, Khuzestan, and Hormozgan have had the highest share of energy consumption. Ilam, Sistan and Baluchistan, Kahgiluyeh and Boyar Ahmad provinces are among the provinces with the lowest energy shares. The industrial province of Yazd, despite having being the fourth place in energy consumption in the industry sector (about 7 percent share) after West Azarbaijan Province, has the lowest average technical efficiency score. This shows that, in this province, planning is required for extensive changes in various sectors of industry in order to increase the efficiency in Energy consumption. The evaluation of the efficiency of the scale of the industries in the country's provinces shows that, in 2014 and the beginning of the law of targeting the subsidies, the industry sector of the provinces of Isfahan, Bushehr, Tehran, Sistan and Baluchistan, Fars, Kermanshah, Gilan, Markazi, Hormozgan worked on an optimal scale, but the other provinces had inefficient scales. Among the inefficient provinces, the intensity of scale inefficiency in Ilam Province was higher than that in the other provinces, which indicates that the size of its production organization is not optimal and it can move towards an efficient scale by changing the size. This is despite the fact that, after the year 2019, a relative improvement in the scale efficiency score occurred for most of the provinces. In the last year, active manufacturing industries in the provinces of Ardabil, Alborz, Bushehr, Tehran, Khuzestan, Sistan and Baluchistan, Kurdistan, Kermanshah, Markazi, Hormozgan and Yazdbenefited from the efficiency of the scale.
Conclusion and Policy Implications: In DEA models, for each inefficient unit, an efficient unit or a combination of two or more efficient units is introduced as a reference unit. In this regard, each inefficient unit should be compared with an efficient unit to reach the efficiency limit. Therefore, the reference unit should be similar in size and structure to the inefficient units that measure it. In this regard, the seven provinces of Ilam, Bushehr, Tehran, Khuzestan, Sistan and Baluchistan, Kohgiluyeh Boyer Ahmad and Hormozgan are considered as reference units for the other provinces of the same level in terms of the size and structure of the industry to improve efficiency. In terms of policy-making, it is suggested that the technical efficiency score of the provinces be supported by the government and its projects for the industry sector through the allocation of low-interest loans, industrial subsidies, tax exemptions, etc.