Tool
The concept of nexus thinking has gained traction amongst the applied research community to examine cross-sector linkages between land, water, and energy strategies. A nexus approach identifies the interactions among sectors to better understand the synergies and trade-offs involved in meeting future resource demands in a sustainable way.
Tool
Social and policy simulations, as well as serious games, are participatory processes through which diverse societal stakeholders collectively explore a complex reality and complex challenges. These participatory processes combine both social and natural science insights to foster experiential learning. They enable participants to make sense of the complexity associated with policy issues, and reflect on system inter-linkages and stakeholder plurality. These methods have become increasingly recognised for informing and guiding policy in complex settings, including sustainable development, climate change mitigation/adaptation and disaster risk reduction.
Model
Two-stage optimal control models are a useful tool to model stochastic shocks, which have the potential to significantly alter the characteristics of a dynamic system, but cannot be controlled by the decision maker. Applications can be found in a wide range of topics including health and environmental economics.
Model
The MODIBE model is a dynamic household model, in which households face stochastic environmental hazards, which can lead to a loss of their wealth. To respond to the risk, households can either relocate to a safer area or undertake preventive measures to protect their physical assets. Both actions require material and immaterial resources, which constrain the household's decision.
Tool
In the IIASA Strategic Initiative fairSTREAM, we create a toolkit of participatory methods that can be adapted to facilitate co-production of knowledge. Co-produced knowledge integrates diverse scientific and social discourses to create relevant and legitimate opportunities in the context of complex problems.
Dataset
This application serves as an expansion of the Bayesian Reconstruction of Populations and Vital Rates by Educational Attainment (BayesEdu) project. Its objective is to integrate existing demographic data to generate accurate estimates of population sizes and vital rates categorized by educational attainment, while also considering associated uncertainties.
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