*Abstract*
Jurisdictional REDD plus policies undertaken at the state or national level are rapidly replacing fragmented local projects at the forefront of conservation efforts. However, their effectiveness remains uncertain, as does the reliability of the mechanisms proposed to measure their impact. To address this, we employ the synthetic control method, which only has one prior application in this domain, to estimate the additional impacts of national REDD plus implementations in Guyana, Gabon, and Honduras. We further assess the assumptions underlying this approach and explore statistical frameworks to enhance confidence in our results.
*Bio*
Onkar is a 2nd year PhD student at the Department of Computer Science & Technology, supervised by Prof. Anil Madhavapeddy and Dr. Sadiq Jaffer. His research interests involve utilising advances in machine learning and causal inference to better understand the impacts of interventions undertaken by governments globally, particularly in the context of evaluating and forecasting progress towards the Sustainable Development Goals. His interests more broadly include spatial statistics, macroeconomics, private markets, and linguistics. He previously received his bachelor’s degree from the University of Tokyo in 2021 and a master’s degree from the University of Cambridge in 2023. Onkar has worked across various firms in the investment and technology industries prior to and during his PhD.
