Providing a framework to estimate ICT contributions to the growth of productivity: Evidence from the Iranian manufacturing industry

Introduction: The impact of ICT on the economic and social development of countries has been studied over the past three decades using different methods and data in different time periods and at national or international levels. Studies show ICT, at the macro level of productivity and economic growth, has been impressive. The ambiguity of ICT productivity was first raised by Robert Solo in 1987. For this reason, it is also known as "solo ambiguity". "We see computers everywhere except in productivity statistics", he said. In the 1980s, most studies reported a negative relationship between productivity at the economy level and the IT workforce. However, in the 1990s, further research findings highlighted the positive and significant effect of ICT on productivity and economic growth. Therefore, the effects and consequences of ICT have been discussed by researchers since the 1990s. The purpose of this study is to examine the productivity growth in all production factors, short-term productivity growth, direct, indirect and total ICT shares as well as the average ICT and non-ICT shares of productivity growth.
Methodology: This research is applied in terms of purpose and descriptive-analytical in terms of data collection. The study aims to explore the relationship between ICT and the productivity growth of all the factors of production. A historical study of the correct measurement of the share of inputs in production shows that there are complex tools and methods in this regard, one of which is growth accounting. Using it, one can calculate the share of technology or the growth of technology in progress, which is equal to the growth of productivity in all the factors of production and is known as "solo waste". Solo waste is the share of productivity in GDP obtained by the difference of the growth of labor and capital from the growth of output. This study evaluates, compares, and analyzes the variables considering growth accounting and the research model of Oliner and Seichel (2002). For this purpose, application is made of the survey results of the industrial workshops of more than ten employees at the level of two-digit codes of the Statistics Center of Iran in the period 2006-2016. The following equations are used to calculate the total productivity growth of the short-term factors of production:
 = - ( + + ) 
   
Also, to calculate the direct and indirect ICT shares, the following equations is used:   , (1+ )
The variables and formulas are fully explained in the text of the article.
First, using the data available on the website of the National Statistics Center of Iran, the nominal value added, the compensation of services and the number of employees, the total price index is extracted by years. Also, using relation (6) the real value added is estimated, and relation (5) calculates the growth of the real value added and the employees. Equation (7) serves to calculate the share of labor force, and then the data on the payment of communications and telecommunications costs are extracted from the site of the Central Bank. Equations (8) and (9) calculate the ICT share and relationship as well as the share of non-ICT, respectively. Equation (9) also extracts the data from the website of the National Center for Total Investment and ICT Statistics.  Relations (10) and (11) along with the explanations of the capital inventory section calculate the growth of real capital inventory of ICT and non-ICT. We now calculate the productivity growth of all the factors of production in the studied years. From Equations (14) and 17-13 and the explanations of the short-term productivity growth, we calculate the short-term productivity growth separately in the studied years. This paper presents the table of the average productivity growth for the total factors of production, the short-term productivity of ICT and their ranks in terms of the type of industry as well as the corresponding charts.
Results and Discussion: Calculations show that only 6 out of 23 industries have experienced total factor productivity growth. The highest productivity growth of the total production factors is in medical, food and beverage, clothing, leather and bags, and in the paper industry, while the lowest is related to tobacco, furniture, printing, chemicals and coke. Calculations also show that 15 out of 23 industries have experienced short-term productivity growth. This shows that the response of most economic sectors to ICT is positive in the short term. The most growth of short-term productivity is related to food and beverage industries, clothing, leather and bags, medicine and paper, but the lowest occurs in the printing, tobacco, tobacco and chemical industries, chemicals, office machinery and recycling. The equation    calculates the direct share of ICT, Equation (16) the indirect share of ICT and Equation (24) the sum of ICT shares. Then, the tables of the average direct, indirect and total ICT shares by years and types of industry are compared. At the end, the table of the average shares of labor force, ICT capital and non-ICT capital are compared according to the type of industry.
Conclusion: The share of ICT in the productivity growth of all the factors of production and short-term productivity growth varies according to the type of industry. This share has been very small and even negative in some years and in some economic sectors. The averages of the direct and indirect shares as well as the total ICT are negligible. Moreover, the indirect share is less than the direct share. The average share of the non-ICT capital is higher than that of labor and the ICT capital during the mentioned period. The difference is significant regarding the average share of the ICT capital.