Small-scale gold mining is important to rural livelihoods in the developing world but also a source of environmental externalities. Incentives for individual producers are the classic policy response for a socially efficient balance between livelihoods and the environment. Yet monitoring individual miners is ineffective, or it is very costly, especially on frontiers with scattered small-scale miners. We ask whether monitoring at a group level effectively incentivizes cleaner artisanal mining by combining lower-cost external monitoring with local collective action.

Human behaviour is of profound significance in shaping pathways towards sustainability. Yet, the approach to understanding human behaviour in many fields remains reliant on overly simplistic models. For a better understanding of the interface between human behaviour and sustainability, we take work in behavioural economics and cognitive psychology as a starting point, but argue for an expansion of this work by adopting a more dynamic and systemic understanding of human behaviour, that is, as part of complex adaptive systems.

This paper examines technical efficiency in farming activities and its implication on forest conservation in Kilosa District. The empirical analysis is based on data collected from 301 households selected randomly from five villages in Kilosa district, of which three villages were under the REDD+ project. Two empirical models were estimated: stochastic frontier Translog production function, and forest resources extraction model.

The vulnerabilities of coastal communities have increased in recent years, as more people have to live in hazard-prone areas due to population growth. The east coast of India is one such vulnerable area that faces the combined challenge of climate risks and poverty. This study identifies the environmental and socioeconomic factors contributing to the resilience building that helped the communities in the study area to cope with cyclone Phailin in 2013 and cyclone Hudhud in 2014. We used questionnaire surveys, GIS and satellite data, and econometric analysis to identify these features.