The sensitivity of the costs of reducing emissions from deforestation and degradation (REDD) to future socioeconomic drivers and its implications for mitigation policy design

Gusti, M., Forsell, N., Havlik, P. ORCID: https://orcid.org/0000-0001-5551-5085, Khabarov, N. ORCID: https://orcid.org/0000-0001-5372-4668, Kraxner, F., & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2018). The sensitivity of the costs of reducing emissions from deforestation and degradation (REDD) to future socioeconomic drivers and its implications for mitigation policy design. Mitigation and Adaptation Strategies for Global Change 24 (6) 1123-1141. 10.1007/s11027-018-9817-9.

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Abstract

Climate change mitigation policies for the land use, land use change, and forestry (LULUCF) sector are commonly assessed based on marginal abatement cost curves (MACC) derived from optimization models or engineering approaches. Yet, little is known about the space of validity of MACCs and how they are influenced by changes in main underlying drivers. In this study, we apply the Global Forest Model (G4M) to explore the sensitivity of MACCs to variation of socioeconomic drivers of deforestation, afforestation, and forest management activities. Particularly, three key factors are considered: (I) wood price, as an indicator of timber market developments; (II) agricultural land price, as a proxy representing the developments on agricultural markets; and (III) corruption coefficient, representing the progress in institutional development and measuring abatement costs use efficiency. The results indicate that the MACCs are more sensitive to the corruption coefficient than to agricultural land price and wood price. Furthermore, we find that the MACCs are more robust with high carbon dioxide (CO2) price and that the sensitivity of the MACCs is higher at low CO2 prices. In general, it can be concluded that when assessing medium-term mitigation policies characterized by low CO2 prices, MACCs need to be developed in-line with institutions currently in place. When designing long-term mitigation policy characterized by high CO2 prices, the role of the analyzed drivers in MACCs estimation is less important.

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