Research data supporting "A placebo approach to evaluate methods of counterfactual estimation for REDD+"

This dataset is the research data supporting the manuscript "A placebo approach to evaluate methods of counterfactual estimation for REDD+". The study evaluates different methods of counterfactual estimation for REDD+ projects using 27 placebo projects, which are randomly chosen areas facing similar deforestation pressures to actual projects but are not yet formally protected or subjected to any REDD+ activities. The dataset consists of polygon shapefiles (*.geojson, compressed in a zip file) of all 27 placebo projects, as well as parquet files (*.parquet) of sampled pixels in the project area and in their matched pixels for each placebo project. Each row represents a sampled pixel, and each column containing the k_luc prefix indicates the JRC-TMF land use class [1] of the pixel in a given year. The proportional change of pixels classified as undisturbed forests over a given time interval is used to calculate annual compound deforestation rates. There are three parquet files for each project: [project ID]_regional.parquet contain sampled pixels in the surrounding landscape of each project, which are used to calculate ex ante forecasts using the regional method; [project ID]_expost_matches.parquet contain sampled pixels in the project area, which are used to calculate ex ante forecasts using the project method, as well as the ex post estimates; [project ID]_matches.parquet contain matched pixels of the sampled project pixels, which are used to calculate ex ante forecasts using the time-shifted matching method. This gives 27 x 3 = 81 files in total. The matching procedures were conducted using the Tropical Moist Forest Accreditation Methodology Implementation code [2], which implements the Canopy PACT 2.0 methodology [3][4]. References: [1] Vancutsem, C et al. (2021). Long-term (1990–2019) monitoring of forest cover changes in the humid tropics. Science advances 7.10 (2021): eabe1603. [2] Dales M, Ferris P, Message R, Holland J, and Williams A (2023). GitHub Repository: Tropical Moist Forest Accreditation Methodology Implementation, https://github.com/quantifyearth/tmf-implementation. commit:7f15246 [3] Balmford, A et al. (2023). PACT Tropical Moist Forest Accreditation Methodology v2.0. Cambridge Open Engage, https://www.cambridge.org/engage/coe/article-details/657c8b819138d23161bb055f. [4] Swinfield, T and Balmford, A (2023). Cambridge Carbon Impact: Evaluating carbon credit claims and co-benefits. Cambridge Open Engage, https://www.cambridge.org/engage/coe/article-details/6409c345cc600523a3e778ae.