Improving Subnational Input–Output Analyses Using Regional Trade Data: A Case-Study and Comparison

Jiang M, Liu L, Behrens P, Wang T, Tang Z, Chen D, Yu Y, Ren Z, et al. (2020). Improving Subnational Input–Output Analyses Using Regional Trade Data: A Case-Study and Comparison. Environmental Science & Technology 54 (19): 12732-12741. DOI:10.1021/acs.est.0c04728.

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Abstract

Environmentally extended input-output analysis (EE-IO) is widely used for evaluating environmental performance (i.e., footprint) at a national level. Many studies have extended their analyses to the subnational level to guide regional policies. One promising method is to embed nationally disaggregated input-output tables, e.g., nesting a provincial level table, into a global multiregional input-output table. However, a widely used approach to environmental assessment generally disaggregates the trade structure at the national level to the provincial level using the same proportions (proportionality assumption). This means that the subnational spatial heterogeneities on international trade are not fully captured. By calculating the Chinese provincial material footprint (MF) based on two approaches-the proportionality assumption and the actual customs statistics-in the same framework, we evaluate the quantitative differences when the proportionality assumption is addressed. By computing MF for 23 aggregated resources across 30 Chinese provinces, our results show for countries with large material flows like China, estimating subnational-level international trade by proportionality assumption may lead to significant differences in material flows at both the disaggregated and aggregated levels. An important follow-up question is whether these differences are also relevant for other footprints.

Item Type: Article
Uncontrolled Keywords: Metals,Fossil fuels,Chemical structure,Extraction,Materials
Research Programs: Energy (ENE)
Depositing User: Luke Kirwan
Date Deposited: 27 Oct 2020 08:22
Last Modified: 27 Oct 2020 08:22
URI: http://pure.iiasa.ac.at/16807

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