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OECD countries and, if they are available, they differsignificantly in the way information is collected.To begin with, to improve the comparability of existing lossdatabases, event classifications should be standardised. Ifevent and hazard type or peril categories diverge from eachother, any subsequent efforts to standardise indicators willbe useless. A consistent peril classification will allow datausers to compare losses from, for example, landslides indatabase A with losses from landslides in database B,thereby illustrating that differences are due to estimationsof loss, not different definitions of landslides or how theywere categorised 301 .Box 4-2. Developing statistics at regional level – cases ofUNESCAP and UNECEWork on standardized methodologies for disaster impactdata has also been undertaken at the regional level.Member States of the United Nations Economic and SocialCommission for Asia and the Pacific (UN-ESCAP) haveestablished an expert group 302 that consists of governmentnominated technical advisors and regional andinternational experts in the field of statistics and disasterrisk management, to work on developing a basic range ofdisaster-related statistics. The Expert Group will bereporting to and obtains the guidance from ESCAPCommittee on Disaster Risk Reduction and Committee onStatistics. The final version of the basic range of disasterrelatedstatistics, i.e. a framework and an implementingguide, will be presented to the ESCAP 72nd Commission in2016 for endorsement.In October 2014, the Bureau of the United NationsEconomic Commission for Europe (UNECE) Conference ofEuropean Statisticians (CES) undertook an in-depth reviewof international work on measuring extreme events anddisasters. The review emphasized several priority actionareas, including: institutional cooperation with mappingagencies to integrate statistical data with geographicalinformation; and the need for common classifications anddefinitions for extreme events and disasters for statisticalpurposes. As a follow-up, the CES Bureau set up a TaskForce on measuring extreme events and disasters, which isplanning to prepare recommendations for nationalstatistical systems by 2017, and will coordinate its workwith the related ESCAP initiative and other internationalorganizations working in this area.Several initiatives have been launched to tackle the issue,including the IRDR Disaster Loss Data (DATA) ProjectWorking Group’s peril classification 303 , OECD work on aaccounting framework for national risk managementexpenditures and losses 304 , and the ESCAP 305 and ECEinitiatives on regional standards (See Box 4-3)76In the Sendai Framework for Disaster Risk Reduction, theConference recommended the establishment of an openendedintergovernmental expert working group supportedby UNISDR for the development of a set of possibleindicators to measure global progress in theimplementation. The working group, set up in May in NewYork, is expected also to consider the recommendations onthe update of the 2009 UNISDR Terminology on DisasterRisk Reduction 306 by December 2016 307 .Extensive riskExtensive risk refers to the risk layer of high-frequency,low-scale losses, and is mainly associated with flash floods,landslides, urban flooding, storms, fires and other localizedevents. Extensive disaster risk is magnified by drivers suchas badly planned and managed urban development,environmental degradation, poverty and inequality,vulnerable rural livelihoods and weak governance 308 .At the time when the HFA was adopted, losses fromextensive risk had not been accounted for in officialnational or international reports, except in a number ofLatin American countries. As a result, this risk layerremained largely invisible and has not been captured byglobal risk modelling. However, since 2007, a sustainedeffort to assist countries in systematically recording localdisaster losses has generated systematic and comparableevidence regarding the scale of extensive risk from over 80countries (Box 4-2).Reports show that the majority of damage and losses since1990 have been associated with extensive disasters inthose countries with consistent data sets (Figure 4-2). In2012, EM-DAT database reported economic losses of US$157 billion, an estimate that is lower than those publishedby Swiss Re (US$186 billion) and Munich Re (US$ 160billion). As an indicative example, if the economic cost ofassets lost in extensive disasters across 85 countries andterritories featured in the Global Assessment Report onDisaster Risk Reduction 2015 (GAR15) is extrapolatedglobally, direct economic losses would be around 60 percent higher than those internationally reported by EM DAT,implying a total of around US$250 billion for 2012. Thistotal loss represents 0.33 per cent of global GDP, 1.4 percent of global capital investment and an annual loss ofmore than US$35 per capita 309 .In particular, such losses represent a serious erosion ofpublic investment in some of those countries with the leastcapacity to invest. For example, the average historicalannual losses from disasters in Madagascar since 2001 areequivalent to around 75 per cent of annual average publicinvestment; in El Salvador, they amount to almost 60 percent, and in Vanuatu they exceed 40 per cent 310 .