جستجوی مقالات مرتبط با کلیدواژه "carbon intensity" در نشریات گروه "اقتصاد"

Along with the increased trade integration of countries and the expansion of international production fragmentation, Global Value Chains (GVCs) amount to a huge part of trade today, and participation in a network of trade partners at downstream and upstream of the value chains brings about considerable potentials such as the improvement of the flow of knowledge and more advanced production technologies and techniques, particularly for developing countries. It would not be unexpected for GVCs and participating in them from an environmental aspect to have potential benefits for countries as well.
In this regard, the present study discusses the role that GVCs play in countries' environmental performance. For this purpose, a sample of 65 developing and 36 developed countries was investigated using spatial panel data econometrics, conditional convergence, spatial auto-correlation, and GVCs participation spillover and direct impacts for countries in the form of south-south, north-south, and north-north bilateral added-value trade. The results indicated that there was spatial auto-correlation and conditional convergence based on GVCs for all countries although they are more intense in the case of north-north trade in developed countries. Besides, participation in GVCs has spillover impacts on the trading partner countries if developed countries are included in the bilateral value-added trade but this impact is not statistically acceptable in south-south trade of developing countries according to estimations. Thus, establishing trading relations with developed countries through GVCs is a potentially beneficial policy to improve developing countries’ environmental performance.

Climate change cannot control unless by reduction of GHG emissions to secure level, therefore it is important to identify driving forces and possible scenarios based on targets.
In this research, the Logarithmic Mean Divisia Index decomposition approach in combination with Extended Kaya Identity (EKI) are applied to investigate five factors could affect emissions during 1971-2012 in Iran. These factors include population, GDPcapita, energy and carbon intensity and share of fossil fuels. Chaining, non-chaining methods and three emission reduction scenarios (4, 8 and 12%) based on Iran INDC forms the other parts of research.
Based on results, carbon intensity, activity effect, and population contribute to increase and share of fossil fuels has a decreasing effect on emissions. The future targets of government should emphasis on change of fuel type and economic development toward low carbon. Chaining analysis could be used as a calendar, show the effect of events on parameters while non-chaining present a clear image by deleting noises. Among proposed reduction scenarios, the best and logical option emphasize on reduction of fossil fuel share (up to 40% compared to 2020) and development of renewable energies. Improvement of carbon and energy intensity (each as 50% compared to 2020) are the next options.