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Harnessing employment-based social assistance programmes to scale up nature-based climate action
Andrew Norton1, Nathalie Seddon2, Arun Agrawal3
1International Institute for Environment and Development, London, UK.
Abstract:
As the severity of the triple challenges of global inequality, climate change and biodiversity loss becomes clearer, governments and international development institutions must find effective policy instruments to respond. We examine the potential of social assistance policies in this context. Social assistance refers to transfers to poor, vulnerable and marginalized groups to reduce their vulnerability and livelihood risks, and to enhance their rights and status. Substantial public funds support social assistance programmes globally. Collectively, lower- and middle-income countries spend approximately 1.5% of their GDP on social assistance annually. We focus on the potential of paid employment schemes to promote effective ecosystem stewardship. Available evidence suggests such programmes can offer multiple benefits in terms of improvements in local ecosystems and natural capital, carbon sequestration and local biodiversity conservation. We review evidence from three key case studies: in India (the Mahatma Gandhi National Rural Employment Guarantee Scheme), Ethiopia (the Productive Safety Nets Programme) and Mexico (the Temporary Employment Programme). We conclude that, to realize the potential of employment-based social assistance for ecosystem benefits it will be necessary to address two challenges: first, the weak design and maintenance of local public works outputs in many schemes, and second, the concern that social protection schemes may become less effective if they are overburdened with additional objectives. Overcoming these challenges requires an evolution of institutional systems for delivering social assistance to enable a more effective combination of social and environmental objectives. This article is part of the theme issue 'Climate change and ecosystems: threats, opportunities and solutions'.
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