CEADS provides the input-output tables for academic users.
We first applied a multi-regional input-output model to ascertain heterogeneity in consumption-based emissions and track carbon flows in the inter-state supply chain, using our newly constructed Indian multi-state input-output table for 2015, based on Flegg location quotient method. We found that household consumption dominated consumption-based emissions at state levels, accounting for 60-78% of total consumption-based emissions, while investment-led emissions were relatively higher in developed regions the in developing regions. More than 30% of consumption-based emissions in developed states were imported from less developed states with higher carbon intensity, indicating a large spillover effect.
Here we propose an entropy-based framework to construct city-level MRIO tables. We demonstrate the new construction method and present an analysis of the carbon footprint of cities in China's Hebei province. A sensitivity analysis is conducted by introducing a weight reflecting the heterogeneity between city and province data, as an important source of uncertainty is the degree to which cities and provinces have an identical ratio of intermediate demand to total demand. We compare consumption-based emissions generated from the new MRIO to results of the MRIO based on individual city input-output tables. The findings reveal a large discrepancy in consumption-based emissions between the two MRIO tables but this is due to conflicting benchmark data used in the two tables.
China multi-regional input-output table for 2012, covering 31 provinces and 42 socioeconomic sectors. The construction of the table is based on the entropy theory and gravity model.
China multi-regional input-output table for 2015, covering 31 provinces and 42 socioeconomic sectors. The construction of the table is based on the entropy theory and gravity model.
China multi-regional input-output table for 2017, covering 31 provinces and 42 socioeconomic sectors. The construction of the table is based on the entropy theory and gravity model.
We propose a partial survey‐based multiple‐layer framework for MRIO table compilation of a Chinese province that distinguishes city‐based regions. This framework can effectively address a large number of data processes and retain consistency between layers. Using the framework, we first compile a nested Hebei‐China city‐level MRIO table and then apply city‐level energy footprint accounting of the North China urban agglomeration.
The dataset consists of value chain trade of 30 provinces in China (excluding Tibet, Taiwan, Hong Kong and Macau).
In this study, we developed a multiregional input‐output table for 31 provinces in China and examined the production‐ and consumption‐based characteristics of Tibet's CO2 emissions in 2012.