Total Factor Productivity Growth in Iran: Presenting a Model with Desirable and Undesirable Outputs
محورهای موضوعی : Decision Analysis
maryam mohebbi
1
,
Hassan Dehghan Dehnavi
2
,
Mozhde Rabbani
3
,
Hamid Babaei Meybodi
4
1 - Department of Industrial Management, Ya.C., Islamic Azad University, Yazd, Iran.
2 - Department of Industrial Management, Ya.C., Islamic Azad University, Yazd, Iran.
3 - Department of Industrial Management, Ya.C., Islamic Azad University, Yazd, Iran.
4 - Department of Industrial Management, Meybod University, Meybod, Iran.
کلید واژه: Efficiency, Total Factor Productivity, Desired Output, Undesirable Output, Data Envelopment Analysis (DEA).,
چکیده مقاله :
The aim of this research is to present a model based on data envelopment analysis with consideration of desirable and undesirable outputs, and calculation of total factor productivity in Iran and the selected countries. To achieve this goal, a method based on data envelopment analysis (DEA) was used with consideration of desirable and undesirable outputs for 42 developing and developed countries in the period from 2012 to 2022. The data analysis was performed in GAMS software. The results of this study showed that the growth of total factor productivity until 2017 was upward in Iran, and shortly after a fluctuated trend was reported. Total factor productivity increased from 0.865 to 1.043 in 2017; that is, in has faced a decrease of 13.5 percent in 2013, and has reached a growth of 4.3 percent in total factor productivity in 2017. On the other hand, the results show that after 2017, the growth of total factor productivity in Iran has been fluctuating. In a way that it has even experienced a decrease of 10 percent and an increase of 14.7 percent in 2022.
The aim of this research is to present a model based on data envelopment analysis with consideration of desirable and undesirable outputs, and calculation of total factor productivity in Iran and the selected countries. To achieve this goal, a method based on data envelopment analysis (DEA) was used with consideration of desirable and undesirable outputs for 42 developing and developed countries in the period from 2012 to 2022. The data analysis was performed in GAMS software. The results of this study showed that the growth of total factor productivity until 2017 was upward in Iran, and shortly after a fluctuated trend was reported. Total factor productivity increased from 0.865 to 1.043 in 2017; that is, in has faced a decrease of 13.5 percent in 2013, and has reached a growth of 4.3 percent in total factor productivity in 2017. On the other hand, the results show that after 2017, the growth of total factor productivity in Iran has been fluctuating. In a way that it has even experienced a decrease of 10 percent and an increase of 14.7 percent in 2022.
Khodabakhshi, M., & Chiragali, Z. (2012). Measuring partial and total factor productivity of the country’s economic sectors. Decision Making and Operations Research, 7(4), 580-569.
Dizji, M. (2018). Forecasting total factor productivity in the Iranian economy. Economic Strategy, 7(25), 45-70.
Fathi, F., & Ghorban, E. (2019). Sustainability of factor productivity in the MENA region with emphasis on ecological footprint. Environmental Sciences, 19(3), 192-177.
Kafaei, S. M. A., & Bagherzadeh, M. (2016). The effect of key macroeconomic variables on total factor productivity in Iran. Economic Research and Policies, 24(79), 215-243.
Bodini, A., Bondavalli, C., & Allesina, S. (2012). Cities as ecosystems: Growth, development and implications for sustainability. Ecological Modelling, 245, 185-198.
Campbell, D. E., & Garmestani, A. S. (2012). An energy systems view of sustainability: Emergy evaluation of the San Luis Basin, Colorado. Journal of Environmental Management, 95(1), 72-97.
Cook, D., Saviolidis, N. M., Davíðsdóttir, B., Jóhannsdóttir, L., & Ólafsson, S. (2017). Measuring countries’ environmental sustainability performance—The development of a nation-specific indicator set. Ecological Indicators, 74, 463-478.
Lemke, C., & Bastini, K. (2020). Embracing multiple perspectives of sustainable development in a composite measure: The Multilevel Sustainable Development Index. Journal of Cleaner Production, 246, 118884.
Lin, S. W., Lo, H. W., & Gul, M. (2023). An assessment model for national sustainable development based on the hybrid DEA and modified TOPSIS techniques. Complex & Intelligent Systems, 1-18.
Kim, Y. E., & Loayza, N. (2019). Productivity growth: Patterns and determinants across the world. World Bank Policy Research Working Paper, (8852).
Li, X., & Su, D. (2022). Total factor productivity growth at the firm-level: The effects of capital account liberalization. Journal of International Economics, 139, 103676.
Ou, C. H., & Liu, W. H. (2010). Developing a sustainable indicator system based on the pressure–state–response framework for local fisheries: A case study of Gungliau, Taiwan. Ocean & Coastal Management, 53(5-6), 289-300.
Olafsson, S., Cook, D., Davidsdottir, B., & Johannsdottir, L. (2014). Measuring countries' environmental sustainability performance–A review and case study of Iceland. Renewable and Sustainable Energy Reviews, 39, 934-948.
Pope, J., Annandale, D., & Morrison-Saunders, A. (2004). Conceptualising sustainability assessment. Environmental Impact Assessment Review, 24(6), 595-616.
Tang, C. S., & Zhou, S. (2012). Research advances in environmentally and socially sustainable operations. European Journal of Operational Research, 223(3), 585-594.
Winfield, M., Gibson, R. B., Markvart, T., Gaudreau, K., & Taylor, J. (2010). Implications of sustainability assessment for electricity system design: The case of the Ontario Power Authority’s integrated power system plan. Energy Policy, 38(8), 4115-4126.
Zhou, H., Yang, Y., Chen, Y., & Zhu, J. (2018). Data envelopment analysis application in sustainability: The origins, development and future directions. European Journal of Operational Research, 264(1), 1-16.
