Global multihazard proportional economic loss risk deciles, v1 (01/01/2000) displays multihazard economic loss as proportions of gross domestic product (gdp). The purpose is to identify areas of the world that are at greater risk of multihazard proportional economic loss. See more information at http://dx.doi.org/10.7927/h4ws8r5b. Dataset summary: global multihazard proportional economic loss risks is a 2.5 minute grid of a multihazard-based economic loss risk as a proportion of the economic productivity of the analytical unit, the grid cell. Representation of multihazard risk is not based on a multihazard index but rather on combinations of hazard risk categories, drought, seismic, and hydro. The drought category includes drought only. The seismic category consists of earthquake and volcano hazards. Cyclones, floods, and landslides are included in the hydro category. For each of the six hazards considered, a binary risk surface is constructed utilizing the three most-at-risk deciles of each hazard's global proportional economic loss risks data set (deciles 8-10). Each of the category risk surfaces are constructed by adding all the relevant hazard high-risk surfaces. These categorical risk surfaces are reclassified into binary high-risk surfaces. The combination of the category risk values forms a three digit identifier for determining those locations that are at higher-risk from multihazards. This data set is the result of collaboration among the columbia university center for hazards and risk research (CHRR), international bank for reconstruction and development/the world bank, and columbia university center for international earth science information network (ciesin). Recommended citation: center for hazards and risk research - chrr - columbia university, center for international earth science information network - ciesin - columbia university, and international bank for reconstruction and development - the world bank. 01/01/2005. Global multihazard proportional economic loss risk deciles. Palisades, ny: nasa socioeconomic data and applications center (sedac). Http://dx.doi.org/10.7927/h4ws8r5b. Accessed day month year.