Input–output analysis of CO2 emissions embodied in trade: The effects of sector aggregation

By Bin Su, H. C. Huang, Beng Wah Ang, Peng Zhou. 2010

319 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/891498889abe74831032dca8dca2975dc84f81ef

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. D. Guan
2. G. P. Peters
3. Robbie M. Andrew
4. Jing Meng
5. Manfred Lenzen
6. Zhu Liu
7. Kuishuang Feng
8. Bin Su

In Environmental Engineering

1. D. Guan
2. G. P. Peters
3. Jing Meng
4. Robbie M. Andrew
5. Kuishuang Feng
6. Zhu Liu
7. Manfred Lenzen
8. Bin Su

Citations in the corpus

• STRUCTURAL DECOMPOSITION ANALYSIS APPLIED TO ENERGY AND EMISSIONS: AGGREGATION ISSUES (2012, methodology): “This is consistent with the findings in Su et al. (2010) and Su and Ang (2010) when the issues of sector and spatial aggregations are analyzed.”
• Carbon emissions of cities from a consumption-based perspective (2019, background): “At the national level, consumption-based carbon emissions have been assessed in many countries, such as Australia [30], China [31,32], Italy”
• China’s provincial CO2 emissions embodied in international and interprovincial trade (2012, background): “Aggregation uncertainty has a significant effect on the calculation of embodied CO2 emissions (Weber, 2008; Thomas, 2009; Su et al., 2010).”
• Revisiting drivers of energy intensity in China during 1997–2007: A structural decomposition analysis (2014, background): “A higher level of sector disaggregation is to be preferred when data availability is not an issue, which can retain full information of data and enhance policy decisions at sectoral scale (Lenzen, 2011; Su et al., 2010).”
• CONSTRUCTING AN ENVIRONMENTALLY-EXTENDED MULTI-REGIONAL INPUT–OUTPUT TABLE USING THE GTAP DATABASE (2011, methodology): “While the GTAP database has been criticized for having poor sectoral detail, the GTAP aggregation of 57 sectors may be adequate for many MRIO applications (Su et al., 2010).”
• AGGREGATION VERSUS DISAGGREGATION IN INPUT–OUTPUT ANALYSIS OF THE ENVIRONMENT (2011, background): “…data towards more detailed environmental data, similar conclusions hold for the reverse 12 This finding is in agreement with results from a study by Su et al. (2010), who also conclude that disaggregation is preferable to aggregation, albeit only on the basis of measuring emissions embodied in…”
• DISAGGREGATING INPUT–OUTPUT MODELS WITH INCOMPLETE INFORMATION (2012, background): “Similarly, Su et al. (2010) showed, using the example of CO2 emissions embodied in the trade of China, how additional information on electricity consumption of each sector and electricity prices can be used to obtain a more accurate estimate for the disaggregated IO table.”
• EFFECTS OF SECTOR AGGREGATION ON CO2 MULTIPLIERS IN MULTIREGIONAL INPUT–OUTPUT ANALYSES (2014, background): “Their findings largely agree with Su et al. (2010) in the number of sectors required; however, this varied strongly across countries.”
• Pattern changes in determinants of Chinese emissions (2017, background): “Su et al (2010), for example, estimated the effects of sector aggregation on CO2 emissions embodied in trade in input-output analysis and indicated that levels around 40 sectors are sufficient to capture the overall share of emissions embodied in a region’s exports.”
• The Heat Is on: A Framework for Measuring Financial Stress Under Disruptive Energy Transition Scenarios (2019, unknown): “, 2015) or inputoutput frameworks (Su et al., 2010).”