surveys, as recommended by De Brauw and Carletto (2012). As of now, there is no best practice in the household surveys realm for collecting this data, whose quality is likely to be compromised by different types of bias (e.g., recall bias, respondent fatigue bias). Testing and validating alternative methods for collecting information on past migration episodes in the context of household surveys is another area of development for migration-related methodological research.<sup>33</sup>

# **_Assessing and overcoming sampling issues_**

Not having a sufficiently large sample of migrants remains the biggest limitation preventing the use of household surveys for studying any type of migration-related issues. As already discussed, this problem originates from the ‘rare event’ nature of the migration decision which is even more pronounced in the case of climate-induced migration. Given that internal migration is much less rare than international migration, LSMS-type surveys have often been used to study internal movements but – despite some exceptions such as Albania (e.g., Mendola and Carletto, 2012) – hardly ever to look at cross-border migration. An easy way to diagnose the magnitude of the ‘rare event’ problem in household surveys is to look at data on the prevalence of migrants (or households with migrants) in the national population relative to the size of the existing sample for the specific survey, as suggested by Bilsborrow (2016). The larger the sample size and the higher the prevalence, the less severe the ‘rare event’ problem.<sup>34</sup> However, should this type of preliminary diagnostics confirm the ‘rare event’ issue, there could still be options for overcoming it. Some of the main options, and related potential innovations going forward, are:

- The use of specialized sampling techniques as proposed by De Brauw and Carletto (2012) remains the most effective solution to the issue. This essentially consists in **oversampling** areas with a high prevalence of migrants which, however, poses challenges due to the limited availability of adequate sampling frames, particularly in developing contexts. This is yet another area where the **integration of household surveys with other data sources** can bring significant advantages by considerably cutting down the costs associated with more traditional updating methods (i.e., door-to-door listing operations). For example, using multi-source frames or leveraging auxiliary information from nonconventional sources (e.g., Earth Observations and geospatial data) can facilitate the implementation of alternative sampling designs that can be used to oversample migrant households (United Nations Statistical Commission, 2021). There are already quite a few examples of studies trying to link survey data with digital trace data to recruit difficult-to-reach respondents (Iannelli et

> 33 Alternative approaches to be tested can include the adoption of roster of moves for shorter recall periods, or relying on household roster updates to capture household members’ moves in-between waves.

> 34 For an application and further practical reflections on the ‘rare event’ issues in household surveys, see subsection 4.1.

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