Technology Decomposition and Energy Intensity in OPEC Countries: DEA-Malmquist Approach
Subject Areas : Operation ResearchMehdi Fallah Jelodar 1 , Somaye Sadeghi 2
1 - Department of Mathematics, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran,
2 - Department of Accounting, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran
Keywords: trade openness, energy intensity, DEA -Malmquist, TFP decomposition,
Abstract :
Reduction of energy intensity through gaining energy efficiency is a global agenda for sustainable development goals. The evidence show that the energy intensities of most energy exporting countries (such as OPEC) have historically been very high compared with energy importing and industrialized economies. Hence, the understanding of the main determinants (or drivers) of energy intensity in energy exporting countries is important for economic researchers and policymakers. Therefore, this paper investigates the role of technology and its components on energy intensity changes in OPEC countries using a DEA-Malmquist over the period of 2000-17. The findings show that technological progress has played a significant role in reducing of energy intensity. Moreover, the results after TFP decomposing using DEA method indicates that the negative effect of technical change on energy intensity is much larger than of the efficiency change effect, Although, the estimated values of these components are is relatively weak. Next, we investigate what is main driving of technological progress in the OPEC countries. The findings imply that trade openness is a main factor to causes to improve the productivity.
Adom, P. K. (2015a). "Asymmetric Impacts of the Determinants of Energy Intensity in Nigeria". Energy Economics, 49(C), 570-80.
Adom, P. K., and Amuakwa-Mensah, F. (2016). "What Drives the Energy Saving Role of FDI and Industrialization in East Africa?" Renewable and Sustainable Energy Review, 65(C), 925-42.
Arellano, M. and Bond, S. (1991), "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations", Review of Economic Studies, 58, 277-297.
Arellano, M., and Bover, O. (1995), "Another Look at the Instrumental Variable Estimation of Error-Components Models". Journal of Econometrics, 68 (1), 29–51.
Baltagi, B. H. )2005(, Econometric Analysis of Panel Data, third ed, John Wiley and Sons Press.
Barasa, L., Vermeulen, P., Knoben, J., Kinyanjui, B. and Kimuyu, P. (2019), "Innovation Inputs and Efficiency: Manufacturing Firms in Sub-Saharan Africa", European Journal of Innovation Management, 22, 59-83.
Blundell, R., and Bond, S. (1998), "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models". Journal of Econometrics, 87(1), 115–143.
Blundell, R., and Bond, S. (2000),"GMM Estimation with Persistent Panel Data: Application to Production Functions, Econometric Reviews," Taylor and Francis Journals, 19(3), 321-340.
Elliott, R. J. R. Sun, P. Y., and Chen, S. Y. (2013). "Energy Intensity and Foreign Direct Investment: A Chinese City-Level Study". Energy Economics, 40(C), 484-94.
Farzipoor Saen, R., Moghaddas, Z., Vaez-Ghesemi, M., and Hosseinzadeh Lotfi, F., (2020), "Stepwise Pricing in Evaluating Revenue Efficiency in Data Envelopment Analysis: Case Study in Power Plants". Scientia Iranica, doi /10.24200/sci.2020.55350.4184.
Fisher-Vanden, K., Jefferson, G. H., Liu, H. and Tao, Q., (2004), "What is Driving China’s Decline in Energy Intensity?" Resource and Energy Economics, 26(1), 77-97.
Fu, X., and Gong, Y. (2011), "Indigenous and Foreign Innovation Efforts and Drivers of Technological Upgrading: Evidence from China". World Development, 39 ,1213-1225.
Fu, X., Pietrobelli, C., and Soete, L. (2011), "The Role of Foreign Technology and Indigenous Innovation in the Emerging Economies: Technological Change and Catching-up". World Development, 39, 1204-1212
Galli, R. (1998). "The Relationship between Energy Intensity and Income Levels: Forecasting Long Term Energy Demand in Asian Emerging Countries", The Energy Journal, 19 (4), 85-105.
Gillingham, K. , Rapson, D., and Wagner, G. (2016), "The rebound effect and energy efficiency policy" Review of Environmental Economics and Policy ,10 (1), 68-88.
Hosseinzadeh Lotfi, F., Ebrahimnejad, A., Vaez-Ghasemi, M., and Moghaddas, Z. (2020), "Data Envelopment Analysis with R" Springer International Publishing.
Huang, J., Du, D. and Hao, Y., (2017). "The Driving Forces of the Change in China Energy Intensity: Empirical Research Using DEA-Malmquist and Spatial Panel Estimations", Economic Modelling, 65(C),41-50.
Huang, J., Hao, Y., and Lei, H. (2018). "Indigenous Versus Foreign Innovation and Energy Intensity in China". Renewable and Sustainable Energy Reviews, 81(P2), 1721-1729.
Im, K. S., Pesaran, M. H. and Shin, Y. (2003). "Testing for Unit Roots in Heterogeneous Panels". Journal of Econometrics, 115(1), 53-74.
Kaldor, N. (1978), Further Essays on Economic Theory, London, Duckworth.
Kishi, K. and Okada, K. (2021), "The impact of trade liberalization on productivity distribution under the presence of technology diffusion and innovation", Journal of International Economics, 128(C).
Lewis, W. A. (1980), "the Slowing Down of the Engine of Growth". American Economic Review, 70(4), 64-555.
Medlock, K. and Soligo, R. (2001), "Economic Development and End-Use Energy Demand", The Energy Journal, 22(2), 77–105. 7.
Roodmn, D. (2009), "How to do xtabond2: An introduction to difference and system GMM in Stata", The Stata Journal, 9(1),86-136.
Samargandi, N. (2019). "Energy Intensity and its Determinants in OPEC Countries", Energy, 186, Article 115803.
Shahbaz, M., Nasreen, S., Ling, C. H. and Sbia, R. (2014), "Causality between Trade Openness and Energy Consumption: What Causes what in High, Middle and Low Income Countries". Energy Policy, 70, 126-143.
Sun, J.W., and Ang, B.W., (2000). "Some Properties of an Exact Energy Decomposition Model". Energy, 25 (12), 1177–1188.
Tarek Atalla, T. and Bean, P. (2017). "Determinants of Energy Productivity in 39 Countries: An Empirical Investigation", Energy Economics, 62, 217–229.
Wooldridge, J. M. (2002), Econometric Analysis of Cross-Section and Panel Data, MIT Press, Cambridge Massachusetts.
Wang, Y. M., and Lan, Y. X., (2011). "Measuring Malmquist Productivity Index: a New Approach Based on Double Frontiers Data Envelopment Analysis", Mathematical and Computer Modelling, 54, 2760–2771.