for surveys other than detailed agricultural surveys, the approach of aggregated land is likely a more practical and affordable option. Similarly, survey practitioners may lean towards the proxy respondent approach, given the apparent ease of implementation relative to the self-respondent approach.

However, the ease of implementation of a given module must be weighed against the data quality implications associated with that choice. Moore (1988), in a literature review on survey response quality of self and proxy respondent approaches, highlighted the lack of studies isolating the impact of proxy response, calling on researchers to further explore this theory through studies carefully designed for this purpose. Since then, research on proxy respondent bias through methodological validation studies has been conducted across multiple sectors. Todorov and Kirchner (2000) found that the use of proxy respondents in representative surveys on disability resulted in systematically biased estimates of national disability rates, with proxy reports estimating 8.8% of people to be experiencing functional limitations, as compared to 16.9% indicated by self-reports (although the direction and magnitude of the bias differed across age group and disability type). In a study on the measurement of income using data from Malawi, Fisher, Reimer, and Carr (2010) found that in 66% of households, the husband underestimated his wife’s income by an average of 47%. This resulted in total household income being underestimated by 26% on average across the full sample when the husband reported income for himself and his wife, as compared to total household income measured through husband and wife self-reports. Kilic et al. (2020) explored the implications of proxy versus self-responding on measuring employment in Malawi, finding that allowing proxy respondents led to underestimates of employment in multiple sectors and with genderdifferentiated magnitudes relative to private self-respondent interviews.

The effect of proxy respondents on the measurement of assets in low-income contexts has recently been explored by the EDGE initiative and the Living Standards Measurement Study-Plus (LSMS+) project.<sup>3</sup> The United Nations Guidelines for Producing Statistics on Asset Ownership from a Gender Perspective (henceforth referred to as ‘UN Guidelines’; UNSD, 2019), based on empirical evidence amassed through the EDGE project, explicitly state: “individual-level data on asset ownership should be reported by self rather than proxy, owing to large discrepancies between proxy and self-responses...”. Evidence from the Uganda Methodological Survey Experiment on Measuring Asset Ownership from a Gender Perspective (MEXA), which fed into the development of the UN EDGE guidelines, illustrates the asymmetric impacts of respondent approach by gender. MEXA found that the use of self-reports increased women’s reported ownership of agricultural land by 5 percentage points relative to proxy reports, while the increase for men’s reported ownership was 10 percentage points (Kilic and Moylan, 2016; UNSD, 2019). In line with this and as part of the LSMS+ project, Kilic, Moylan, and Koolwal (2020) found that the use of proxy respondents relative to self-respondent implementation resulted in higher rates of exclusive ownership of agricultural land for men, and lower rates for women. Thus, these gender-differentiated biases based on respondent strategy may not only lead to inaccurate estimates of land tenure for the population at large, but they also have the potential to distort estimates of the gender gap in rights.

On the relationship between data quality and level of data collection, there is a dearth of research on the implications of collecting land tenure data at the parcel level vis-à-vis the aggregate level. However, related research on the effects of aggregation raises concerns for data quality implications and motivates the need for methodological validation. Research by Beegle et al. (2012), for example, explored the impacts of the level of detail in a consumption questionnaire on the resulting consumption estimates. The a priori assumption is that greater levels of detail, specifically a longer list of specific consumption items, trigger respondents’ memories and prevent

> 3 For reports on the LSMS+ surveys in Tanzania, Malawi, Ethiopia, and Cambodia, see Hasanbasri et al. (2021a) and Hasanbasri et al. (2021b).

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