Conservation Impact Evaluation Using Remotely Sensed Data

48 Pages Posted: 9 Aug 2022 Last revised: 21 Aug 2023

See all articles by Alberto Garcia

Alberto Garcia

Yale University - School of the Environment

Robert Heilmayr

University of California, Santa Barbara (UCSB)

Date Written: August 2, 2022

Abstract

The application of quasiexperimental impact evaluation to remotely sensed measures of deforestation has yielded important evidence detailing the effectiveness of conservation policies. However, researchers have paid insufficient attention to the binary and irreversible structure of most deforestation datasets. Using analytical proofs and simulations, we demonstrate that many commonly employed econometric approaches are biased when applied to binary and irreversible outcomes. The significance, magnitude and even direction of estimated effects from many studies are likely incorrect, threatening to undermine the evidence base that underpins conservation policy adoption and design. To address these concerns, we provide guidance and new strategies for the design of panel econometric models that yield more reliable estimates of the impacts of forest conservation policies.

Keywords: Deforestation, Conservation, Impact evaluation, Remote sensing

JEL Classification: Q23, Q24, Q57, C23

Suggested Citation

Garcia, Alberto and Heilmayr, Robert, Conservation Impact Evaluation Using Remotely Sensed Data (August 2, 2022). Available at SSRN: https://ssrn.com/abstract=4179782 or http://dx.doi.org/10.2139/ssrn.4179782

Alberto Garcia (Contact Author)

Yale University - School of the Environment ( email )

New Haven, CT
United States

Robert Heilmayr

University of California, Santa Barbara (UCSB) ( email )

South Hall 5504
Santa Barbara, CA 93106
United States

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