 The higher flexibility offered by remote data collection tools should also be exploited to **investigate migration-related outcomes of different types of climate shocks** that might interest survey locations at large-scale, including fast-onset ones. For example, these data collection tools can be quickly adapted to conduct a partial survey focused only in the areas of a given disaster, which can then be merged with other data waves without compromising the implementation or representativeness of the core survey. This work should build upon the lessons learned from recent experiences with the COVID-19 pandemic,<sup>30</sup> which have provided actionable tools such as rapid phone-survey modules that may outlive the pandemic itself.

  As the use of remote data collection technologies comes with multiple statistical challenges (i.e., non-representativeness, attrition, non-response, and selection bias) more research should be conducted to **assess the extent of statistical challenges and validate methods for overcoming them** . Again, starting with and moving beyond the COVID-19 experience may be the key to solving challenges related to overly specific migration-related survey tools (for instance, by complementing standard face-to-face representative surveys with _ad hoc_ followup phone-survey interviews for selected subgroups, and then analyzing differences with the full face-to-face sample to econometrically address selection bias issues).

Improving **tracking** in longitudinal household surveys is also key for more accurate migration measurement, especially for internal migration. The primary benefit of an effective tracking strategy is to reduce attrition in panel surveys. But if the right information is collected as part of tracking (for example, about the motives of moving<sup>31</sup> ), it can also provide direct observation of migratory flows of households and individuals within the original survey sample. This is also an area where the use of new technologies and data sources can be highly beneficial. In general, augmenting panel survey data with new types of data like digital trace data would allow the collection of information in domains that are normally arduous to cover in household surveys due to respondent burden and recall issues, such as geographic moves and migratory events.<sup>32</sup>  Complementary to (longer-term) efforts for more and better tracking, the collection of (full or partial) **migration histories** of selected household members is an effective – and more immediate – solution for increasing the availability of migration data in panel household

> 30 This includes the adoption of new best survey practices introduced as part of these experiences such as the systematic elicitation of contact information of all household members which is a key prerequisite for implementing remote follow-up surveys. 31 In a recent working paper exploiting LSMS-ISA panel data to study the effects of cumulative climate shocks on long-term migratory flows in Sub-Saharan Africa, Di Falco et al. (2022) point out that the information about the motives of moving is only available for two of the five countries included in their analysis ( _i.e._ , Ethiopia and Nigeria).

> 32 This type of applications would require consent from survey participants and possibly participation in additional tasks with the risk of increasing panel dropouts (Trappmann et al., 2022), a risk that, however, could be outweighed by the potential gains in using these data.

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