Handbook of Global Research and Practice in Corruption
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Handbook of Global Research and Practice in Corruption

Edited by Adam Graycar and Russell G. Smith

Corruption is a global phenomenon with costs estimated to be in the trillions of dollars. This source of original research and policy analysis deals with the most important concepts and empirical evidence in foreign corrupt practices globally.
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Chapter 8: Corruption in REDD+ Schemes: A Framework for Analysis

Peter Larmour


Peter Larmour REDD – reducing carbon emissions from deforestation and forest degradation – promises to be a cheap and effective way of reducing the amount of carbon in the atmosphere. First proposed by the governments of PNG and Costa Rica in 2005, it has been gaining international favour, particularly after the Copenhagen Conference. REDD+ includes other measures to enhance forest carbon stocks. One REDD mechanism – payment for Environment Services (PES) – envisages paying governments or landowners for not cutting down trees (Angelsen, 2009; Howes, 2009 for PNG). The idea of REDD+ is simple to explain, but it also seems simple to cheat. The international rules are still unclear and – being international – will be hard to enforce. Once in place, the complexity of REDD+ regulations will create its own opportunities for corruption. Markets in carbon credits already provide opportunities for speculation by ‘carbon cowboys’ (Filer, 2010). The huge flows of money envisaged are attractive to criminals. In any case, forestry has a poor track record for illegality, including corruption. Some of the countries signing up for REDD have poor reputations for corruption in government. There is a small but growing literature on corruption risks in REDD schemes, often starting from the experience of illegal logging (Tacconi et al., 2009; Brown, 2010; Bofin et al., 2011). Transparency International’s upcoming Global Corruption Report will focus on climate change. This chapter proposes a framework summarizing types of diagnoses and cures for corruption and applies it to REDD+1. First, to set the scene, it identifies some similarities and...

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