The expectations of and covariances between carbon footprints

Journal Article (2019)
Author(s)

João F. D. Rodrigues (Universiteit Leiden)

Rong Yuan (Universiteit Leiden, Chongqing University)

Hai-Xiang Lin (Universiteit Leiden, TU Delft - Mathematical Physics)

Research Group
Mathematical Physics
Copyright
© 2019 João F. D. Rodrigues, Rong Yuan, H.X. Lin
DOI related publication
https://doi.org/10.1080/09535314.2019.1659757
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 João F. D. Rodrigues, Rong Yuan, H.X. Lin
Research Group
Mathematical Physics
Issue number
2
Volume number
32 (2020)
Pages (from-to)
192-201
Reuse Rights

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Abstract

Carbon footprints and other environmentally extended input–output indicators are obtained as aggregations of emissions embodied in supply chains (EESCs), which express the emissions occurring in a specific production activity to satisfy a given volume of final demand. Here we derive theoretical approximations of the expectations of and covariances between EESCs, as a function of the expectations of and covariances between source data (technical coefficients, emission coefficients and final demand volumes) through a Taylor expansion. We report an empirical test of those approximations, using a sample of 5 global multi-regional input–output models in the year 2007, of which we extract 22 single-region input–output systems with 17 sectors. We find that approximations of multipliers perform better than those of EESC, and approximations of expectations perform better than those of covariances.