Cited by 230Conservation, Biodiversity, and Resource ManagementLand Rights and ReformsIndigenous Cultures and History

The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index; 6 of the 29 sources its claims cite were checked for support.

Collective property rights reduce deforestation in the Brazilian Amazon

Open access
Baragwanath, Kathryn, Bayi, Ella·2020·Proceedings of the National Academy of Sciences

Abstract

Significance: Deforestation in the Amazon has reached record highs in 2019 and poses a serious threat to climate change. In Brazil, about 2 million hectares of indigenous land are still awaiting homologation, and thus do not have their full property rights. We find that granting property rights significantly reduces the levels of deforestation inside indigenous territories, and the results are of significant orders of magnitude. Our local effects indicate that areas of land right inside a territory with full property rights experience significantly less deforestation than those right outside of the border. Collective property rights might thus provide an effective way to reduce deforestation in the Brazilian Amazon.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using satellite data and a regression discontinuity design, the paper finds that granting full collective property rights (homologation) to indigenous territories in the Brazilian Amazon significantly reduces deforestation inside their borders. The effect is absent in territories without full property rights, suggesting homologation is a cost-effective forest-preservation tool.

Key findings

  • Observations inside territories with full property rights show a significant decrease in deforestation, while the effect does not exist in territories without full property rights.
  • Homologation is associated with about a 2-percentage point decrease in deforestation right at the border; against baseline deforestation of around 3%, this represents a 75% decrease. After homologation, deforestation in the RDD buffer fell from 3% to 1%.
  • Nonhomologated territories show no significant discontinuity; before-homologation estimates are much smaller than after-homologation estimates (e.g., in Table 1, before homologation 4th-order optimal bandwidth estimate −0.17 vs after homologation −1.99).
  • The paper estimates that the standstill in homologation under Temer and Bolsonaro could be responsible for an extra 1.5 million hectares of deforestation per year.

Methods

  • Uses NASA VCF5KYR fractional vegetation cover data at ~4 km × 4 km resolution, yearly 1982–2016, creating a panel of 30,699 pixels and 1,074,465 observations across 245 indigenous territories.
  • Combines a geographic regression discontinuity design around territory borders (12-km buffer inside/outside) with the orthogonal timing of homologation, comparing before/after and inside/outside, and using nonhomologated territories as controls/placebo.
  • Main estimates use RDD with fourth-order polynomial and MSE-optimal bandwidth, robust standard errors clustered at indigenous territory level; robustness checks vary covariates, bandwidths, functional forms, time windows, and the BenYishay et al. sample.

Limitations

  • Paper-stated: estimates are local average treatment effects; the design cannot rule out leakage, and the authors cannot make causal claims about total deforestation levels in the Amazon as a whole. They report limited evidence of leakage inside buffers: the difference in deforestation right outside borders before and after homologation is less than 0.2 percentage points, compared with the 2-percentage point reduction.
  • Paper-stated: VCF5KYR has lower spatial resolution than Hansen data; years 1994 and 2000 are missing and imputed as the average of adjacent years; spatially explicit poverty/population covariates are limited (nightlights from 1990s, population from 2000 in 5-y intervals), so main models use mainly geological/physical covariates, with robustness checks including nightlights and GPW yielding somewhat smaller but significant results.
  • Evident from text: the RDD is boundary-local and balance tests show a jump at the cutoff for elevation (though other geographic variables appear balanced and covariates are included); territories in the first demarcation step lack geocoded boundaries, reducing the number analyzed.

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Integrity signals

Registry

Crossref · 10.1073/pnas.1917874117

Cites

46 of 46 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

13 Own interpretation · 12 Own result · 11 Own method · 7 No full text of the sources · 3 Not checked yet · 2 Partly supported · 2 Sources not found · 2 No basis given · 1 Supported · 1 Couldn’t confirm · accuracy not yet measured

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Show all 31 claims

  • It may state two separate claims as one. 16
  • Probably not a substantial claim. 9
23 of 23
  • The paper relies on this without support.

    The potential outcomes of deforestation are continuous at the indigenous territory border, so pixels just inside and outside the border are comparable except for property rights.

    “The RDD ensures that we are comparing pixels that are almost identical to each other, other than for the fact that some are inside homologated territories while others are not.”
  • The paper relies on this without support.

    Demarcated but nonhomologated territories are valid control groups for similar demarcated and homologated territories.

    “Plots of land that have been demarcated but not homologated serve as good control groups for those similar plots that have been demarcated and homologated.”
  • The authors state this as an assumption.

    Possible confounders are continuous around the cutoff; assignment to treatment relies only on the running variable, distance to border, and is orthogonal to any other variable that might be generating deforestation.

    “An important assumption of the regression discontinuity model is that possible confounders should be continuous around the cutoff. In other words, assignment to treatment should rely only on the running variable, distance to border, and be orthogonal to any other variable that might be generating the outcome, in this case, deforestation.”
  • The paper relies on this without support.

    Observations right inside the territory are similar to observations right outside of the territory.

    “Observations right inside the territory are expected to be similar to observations right outside of the territory.”
4 of 4

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Citations

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Metadata

Authors
Baragwanath, K., & Bayi, E.
Affiliations
  • University of California San Diego (US)
  • Columbia University (US)
Corresponding author
Baragwanath, Kathryn
Venue
Proceedings of the National Academy of Sciences
Published
2020-08-11
Volume
117
Issue
34
Pages
20495-20502
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W3048450790
Cited by
230
References
42
Citations by year
2026: 36 · 2025: 47 · 2024: 32 · 2023: 44 · 2022: 40 · 2021: 24 · 2020: 6
FWCI
10.60
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Conservation, Biodiversity, and Resource Management
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Land Rights and Reforms
  • Social Sciences › Anthropology › Indigenous Cultures and History
Keywords
deforestation, indigenous property rights, indigenous territories, common-pool resources, homologation, land tenure, Amazon rainforest, climate change mitigation, forest conservation, indigenous rights, Brazil
MeSH terms
Indigenous Peoples, Brazil, Conservation of Natural Resources, Humans, Human Rights, Ownership, Rainforest

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