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Mitigation and Adaptation Strategies for Global Change

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01.01.2022 | Original article

The economic impact of a deep decarbonisation pathway for China: a hybrid model analysis through bottom-up and top-down linking

verfasst von: Xin Su, Frédéric Ghersi, Fei Teng, Gaëlle Le Treut, Meicong Liang

Erschienen in: Mitigation and Adaptation Strategies for Global Change | Ausgabe 1/2022

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Abstract

The development of mid-century low-emission development strategies is critical to guiding national actions on long-term mitigation. One of the key concerns in developing mitigation strategies is the cost of the low-carbon transition. In this study, we estimate the macroeconomic cost of a deep decarbonisation pathway for China, by integrating an energy-systems optimisation model with an economic model through hard linking. Our results indicate that deep decarbonisation increases the energy expenses of Chinese households in the mid-run due to the higher cost of electricity. However, firms will benefit from moderate decarbonisation as a result of a reduction in coal and oil consumption. As a result, energy-efficiency improvements lead to a reduction in firms’ total energy costs, partially compensating the crowding-out effect of low-carbon investments on general productive capital. Our mitigation scenario has therefore a small macroeconomic cost compared to business as usual, equal to a lag in the growth of less than one year in 2050.

Vorheriger Artikel Can remittances contribute to financing climate actions in developing countries? Evidence from analyses of households’ climate hazard exposure and adaptation actors in SE Nigeria

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See https://unfccc.int/process/the-paris-agreement/long-term-strategies.

Compared to MACRO, KLEM covers international trade and input–output loops, although at a level of aggregation that forbids the explicit modelling of the influence of shifting sectoral contributions to non-energy activity. We postpone further publication analyses based on coupling China-MAPLE to a multisector generalisation of KLEM.

One simple example to consider is that of the combined constraints of a minimum capacity of renewable power generation and a maximum capacity of coal power generation. As long as the cap on coal capacity is not reached, the marginal cost of electricity is that of coal generation and depends on whether the existing coal plants are or are not operating at full capacity (additional investment required or not). This marginal cost may be far below the average cost of power supply, which also reflects the specific costs of the renewable quota.

Our numerical method would guarantee optimality from the point of view of the minimisation of technical costs only, under the constraint of the converged level of economic activity. We would not have any guarantee that the macroeconomic costs of the transition would be minimum.

For a recent survey on AEEI, see Bataille and Melton (2017). KLEM-CHN’s trade-off between aggregate value-added and energy and its specification of AEEI are similar to those of Bataille and Melton’s CGE model.

Our choice of “KL-E” rather than “KE-L” nesting reflects the recommendation of van der Werf (2008) and the most common practise for both China and other country models. Feng and Zhang (2018) advocate “KE-L” nesting in the case of China only because they assess several estimations collectively, whereas their best estimation of “KL-E” nesting performs slightly better than their best estimation of “KE-L” nesting.

We keep \(u\) explicit for further explorations with equilibrium unemployment like those of Soummane et al. (2019) on Saudi Arabia.

With kind permission from the authors.

Combet et al. (2014) and Le Treut (2019) detail similar hybridisation in the case of France. The particulars of our procedure are available upon request.

The consumption of public institutions is registered as intermediate consumption by the public services sector, which is aggregated to the non-energy good in our 2-sector dataset.

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Titel: The economic impact of a deep decarbonisation pathway for China: a hybrid model analysis through bottom-up and top-down linking
verfasst von: Xin Su
Frédéric Ghersi
Fei Teng
Gaëlle Le Treut
Meicong Liang
Publikationsdatum: 01.01.2022
Verlag: Springer Netherlands
Erschienen in: Mitigation and Adaptation Strategies for Global Change / Ausgabe 1/2022
Print ISSN: 1381-2386
Elektronische ISSN: 1573-1596
DOI: https://doi.org/10.1007/s11027-021-09979-w

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