Price Incentives and Unmonitored Deforestation: Evidence from Indonesian Palm Oil Mills

Guye, Valentin; Kraus, Sebastian

doi:10.2139/ssrn.4120270

Cited by 1 publication

(3 citation statements)

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“…Palm oil sourcing zones by island were determined using inverse distance weighting with a sourcing distance of 38 km, based on the 97.5th percentile of the distance between oil palm plantations and the nearest palm oil mill. Past work has used this radius approach [2,25,46,47]. Our identified sourcing distance of 38 km aligns with previous estimates, e.g.…”

Section: Determining Grid-cell Exposure To Zdcssupporting

confidence: 86%

“…Our identified sourcing distance of 38 km aligns with previous estimates, e.g. [2] used 30 km for Sumatra, and Starling 6 uses 2, 20, and 50 km [47]. We used an inverse distance weighting method to assign ZDC scores to all grid cells within each mill shed based on each mill point's owner and buyer ZDC score and analyzed ZDC owner and buyer scores separately.…”

Section: Determining Grid-cell Exposure To Zdcsmentioning

confidence: 81%

“…The expansion of oil palm plantations has been a key driver of deforestation in Indonesia in the past two decades [1,2]. Due to increasing global demand, palm oil production is expected to lead to the loss of 13% of Indonesia's remaining natural forests by 2050 if historical trends persist [3].…”

Section: Introductionmentioning

confidence: 99%

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How well does the implementation of corporate zero-deforestation commitments in Indonesia align with aims to halt deforestation and include smallholders?

Chandra,

Garrett,

Carlson

et al. 2024

Environ. Res. Lett.

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In response to growing scrutiny surrounding commodity-driven deforestation, companies have introduced zero-deforestation commitments (ZDCs) with ambitious environmental and social targets. However, such initiatives may not effectively reduce deforestation if they are not aligned with the spatial extent of remaining forests at risk. They may also fail to avert socio-economic risks if ZDCs do not consider smallholder farmers’ needs. We assess the spatial and functional fit of ZDCs by mapping commodity-driven deforestation and socio-economic risks, and comparing them to the spatial coverage and implementation of ZDCs in the Indonesian palm oil sector. Our study finds that companies’ ZDCs often underperform in four areas: traceability, compliance support for high-risk palm oil mills, transparency, and smallholder inclusion. In 2020, only one-third of companies sourcing from their own mills, and just 6% of those sourcing from external suppliers, achieved full traceability to plantations. Comparing the reach of ZDCs adopted by downstream buyers with those adopted by mill owners located further upstream, we find that high-quality ZDCs from buyers covered 62% of forests at risk, while mill owners’ ZDCs only covered 23% of forests at risk within the mill supply base. In Kalimantan and Papua, the current and future deforestation frontiers, the forests most at risk of conversion were predominantly covered by weak ZDCs lacking in policy comprehensiveness and implementation. Additionally, we find that only 46% of independent smallholder oil palm plots are in mill supply sheds whose owners offer programs and support for independent smallholders, indicating that smallholder inclusion is a significant challenge for ZDC companies. These results highlight the lack of spatial and functional alignment between supply chain policies and their local context as a significant gap in ZDC implementation and a challenge that the EU Deforestation Regulation will face.

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Section: Determining Grid-cell Exposure To Zdcssupporting

confidence: 86%

Section: Determining Grid-cell Exposure To Zdcsmentioning

confidence: 81%