Another often overlooked yet complementary aspect of climate migration studies is climate-induced immobility traps. This refers to the same climate shocks possibly creating the opposite outcome by reinforcing pre-existing vulnerabilities and aggravating liquidity constraints, forcing poorer households to stay due to a lack of necessary resources to cover the costs of migration. Under this alternative scenario, climate change would reinforce existing and generate new local poverty traps and vulnerability pockets in the most affected (especially rural) areas, which should make climate-related immobility as much of a concern as mobility (Findlay, 2012; Letta et al., 2023).

Gaining a firm understanding of these complex dynamics requires clarity about what we need to measure, at what scale and how and, more importantly, filling data gaps on climate migration at the micro level. This not only involves providing more accurate quantification of migration inflows and outflows, but also improving the ability to properly characterize the phenomenon and empirically assess the ultimate socioeconomic and welfare impacts and how they differ across population subgroups (e.g., What type of migration does climate change induce? How do those migrating differ from those who stay? What channels and contextual factors mediate different migration responses and the realization of different outcomes, and how do they interact with each other?). Conducting these measurements requires an adequate amount of sufficiently disaggregated information on multiple socioeconomic aspects and living standards. It also requires this information to be collected in a consistent and systematic way, made available and accessible in a timely manner, and updated regularly. Addressing these data needs in the immediate future is instrumental to building the evidence base needed to inform policies and development interventions aimed at improving climate change adaptation and promoting better forms of mobility.

Household surveys are one of the data sources traditionally used to measure and study migration. Despite some recognized limitations, _multi-topic_ household surveys hold great potential when it comes to analytically addressing complex, multidimensional phenomena such as climate and migration, which require data on multiple livelihood dimensions and possibly over extended periods of time. When georeferencing is used in household surveys it allows for integration with other data sources, offering even greater potential to achieve higher levels of accuracy and granularity at lower cost as well as to increase the relevance of survey data production and their downstream reuse (e.g., for ground-truthing and calibration purposes).<sup>6</sup> In the last few years there has been a progressive push towards repositioning household surveys in the face of an evolving data environment and new demands for policy-relevant data in different fields (Carletto and Gourlay, 2019; Carletto, 2021; United Nations Statistical Commission, 2021). The COVID-19 pandemic accelerated this process and proved that household surveys are flexible enough instruments to respond effectively to modern data collection challenges. New modes of data collection as well as integration with alternative data sources have been tested and validated. Leveraging technological innovations, more can be done in the near future to improve survey methodologies and data collection methods (Zezza et al., 2022;

> 6 This, of course, must be done in compliance with adequate security standards to protect confidentiality (United Nations Statistical Commission, 2021).

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