Disaster risk governance: Unlocking progress and reducing risk

The call and the analysis presented here responds to an identified need for more comparative studies on how governance systems and development situations have shaped progress on disaster risk management (DRM). This paper reviews a selected number of different governance systems in terms of their institutional structures (centralized and decentralized); distribution of power and decision-making authority; capacities and resources; and role of different stakeholders among other characteristics.

The analysis draws on a variety of governance, risk management and adaptation indices as well as secondary literature from across a range of countries and contexts. It assesses different dimensions of disaster risk governance (DRG) and how these have developed since 2005 when the Hyogo Framework for Action (HFA) was agreed by 168 governments at the World Conference on Disaster Reduction. The aim of the paper is not to test or evaluate the effectiveness of the HFA, but rather to assess the general direction of change with regard to the institutional, policy, and legislative environment, and to identify some of the key drivers of progress towards developing more proactive measures to reduce disaster risk and avoid the creation of risk in the future. 

– UNDP, 2014

Are you sure you want to delete this "resource"?
This item will be deleted immediately. You cannot undo this action.
File Name File Size Download
disaster_risk_governance.pdf

Related Resources

Report
12 Jul 2018
In 2015 FAO issued its first report on The Impact of Disasters on Agriculture and Food Security, exploring the negative effects of naturally-induced and climate-related disasters ona agriculture. Against the backdrop of increasingly pressing challeng...
Tags: Report, Business Preparedness, Capacity Building for Disaster Risk Management
Report
22 Sep 2017
“Can CAP help persons with disabilities calling for rescue or receiving public alerts?”presented September 21, 2017by Stefano Marsella
Tags: Report, Early Warning Systems
Research
13 Mar 2024
The present study proposed a novel interpretable machine learning approach to predict household-level evacuation decisions by leveraging easily accessible demographic and resource-related predictors, compared to existing models that mainly rely on ps...
Tags: Research, Hurricane / Typhoon / Cyclone, Mobile Technology
Scroll to Top