Technical Efficiency in Iran’s Industry Sector: A Stochastic Frontier Analysis (SFA) Approach (in Persian)

Mansour Asgari (m.asgari@itsr.ir)
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Mansour Asgari: Assistant Professor, lInstitute for Trade Studies and Research (ITSR), Tehran, Iran.

The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی و بودجه), 2019, vol. 24, issue 3, 61-85

Abstract: Nowadays, the most important factor affecting production is efficiency, which recovers economic performance, adjusts prices, enhances competitiveness, and improves social welfare and growth sustainability by influencing the production level. This paper aims to estimate the technical efficiency of production in Iran's industrial sector by implementing Stochastic Frontier Analysis (SAF); To this end, the Translog Function is used to estimate the production and technical performance of the Iranian industry sector in terms of four-digit International Standard Industrial Classification (ISIC) codes for the period 2010-2018. Accordingly, the panel data technique is applied to estimate the technical efficiency and production function Frontier Production Functions, the estimator of maximum likelihood variables of using value-added variables, labor force, capital, and energy based on four-digit ISIC codes. The results show that the chemical, petroleum, and coal industries ranked first in efficiency; textile manufacturing, clothing industry, wood, and cork industry, manufacture of articles of straw and plaiting materials, and paper and paper products ranked second in efficiency; Coke production and refined petroleum products, chemicals and chemical products, and manufacturing other non-metallic mineral products ranked third in efficiency; and lastly, manufacturing basic metals and fabricated metal products, except machinery and equipment, ranked as fourth.

Keywords: Stochastic Frontier Analysis (SAF); Technical Efficiency; Industry Sector; Maximum Likelihood Estimation; Panel Data. (search for similar items in EconPapers)
JEL-codes: C23 D24 Q12 (search for similar items in EconPapers)
Date: 2019
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