explicit in collated records as part of disaster inventories but limit the comparability of data across different events and contexts.<sup>37</sup> Within the same survey, information collected in microdata is typically harmonized and comparable across events covered. While microdata are subject to differences in survey and questionnaire design across contexts, such differences are usually explicit. Analysts can therefore take these differences into account when making comparisons and there is scope for harmonization across contexts as in the case of the LSMS-ISA suite of surveys.

# **Geographical differences**

Many of the previously discussed sources of inaccuracies in estimates of disaster incidence and severity are more pronounced in low- and middle-income countries (LMICs).<sup>21,30,37,42</sup> This goes in particular for data from disaster inventories that depend on the comprehensiveness of coverage in the underlying data sources they draw on. For example, the density of information on shocks and natural disasters is lower in LMICs meaning that shocks are more likely to go unreported, information is more likely to be incomplete or inaccurate, poor and marginalized population groups are more likely not to be covered, and the impact on them is more likely to be underestimated due to a higher share of uninsured damages and a lower value of affected assets. On the side of microdata, surveys in high-income countries may provide more accurate data due to the availability of more sophisticated measurement approaches and higher levels of education among respondents which may positively affect the accuracy of self-reported information.

|**Dimension**|**Disaster Inventories**|**Microdata**|
|---|---|---|
||**Coverage**||
|**Shock coverage**<br>(Threshold and hazard<br>bias)|• Subject to reporting in aggregate data<br>sources and reports<br>• Salient shocks likely covered but data<br>less sensitive to idiosyncratic or small<br>shocks<br>• Coverage varies by shock type|• Based on “grassroots” reports elicited<br>from those affected by shocks<br>• Granular and able to cover small and<br>localized shocks<br>• Shock recording subject to questionnaire<br>design (list of shocks, number of shocks<br>recorded)|
|**Population coverage**<br>(Population coverage<br>biases)|• Coverage<br>depending<br>on<br>comprehensiveness<br>of<br>coverage<br>in<br>underlying data sources (e.g. news<br>reports) but not limited to a specific<br>population of interest<br>• under-coverage<br>of<br>poor<br>and<br>marginalized population groups within<br>countries likely|• Limited to (stratified) sample of target<br>population<br>• Potential for gaps in coverage wherever<br>shock impacts not well represented by<br>sample<br>• Poor and marginalized population groups<br>explicitly covered|
|**Temporal coverage**<br>(Temporal coverage<br>biases)|• Continuous coverage but subject to<br>improvements in quality of reports in the<br>long run|• Intermittent coverage limited to years in<br>which survey was conducted and/or<br>recall period of survey questions|
||**Detail and accuracy**||
|**Detail of available**<br>**information**<br>(Missingdata biases)|• Dependent on information reported in<br>sources, limited detail and frequently<br>missing information in some dimensions|• High level of detail and completeness of<br>data collected, even for small and|

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