More recently, some survey programs have started gathering data on intra-household patterns of ownership and use rights for selected assets. This includes surveys conducted under the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) initiative, which include a series of questions about which members of the household (co-)own each of the household’s plots and nonagricultural household enterprise, and their participation in various aspects of decision-making. LSMS-ISA data have stimulated a rich empirical literature on gender inequality in African agriculture (e.g. O’Sullivan et al 2014; Kilic et al 2015), including differences in land ownership between males and females (e.g. Doss et al 2015; de la O Campos et al 2015; Slavchevska et al 2017).

An alternative data source to study gender gaps in property ownership is the DHS program, where surveys conducted under the 6<sup>th</sup> and 7<sup>th</sup> rounds (from 2010 onwards) include the questions (a) “do you own any land either alone or jointly with someone else?” and (b) “do you own this or any other house either alone or jointly with someone else?” in the women’s and men’s questionnaires. For the analysis in this paper, DHS have a couple of advantages over the LSMS-ISA data. First, as of June 2017, when we completed the analysis, DHS questions on individual land (housing) ownership were available for 27 (28) African countries<sup>9</sup> (see Table A1, appendix), compared with just 8 countries covered by the LSMS-ISA program. Second, DHS surveys collect information on intra-household ownership of land and housing, which both fall under the category of immovable property. Conversely, LSMS-ISA surveys (apart from the recent IHS4 2016/17 in Malawi) focus on intra-household ownership and decision making in terms of agricultural land, livestock and non-farm enterprises – which are important assets but accumulated through rather different channels and hence difficult to synthesize into a single narrative. Third, DHSs generally field individual-level survey modules (i.e. the women’s and men’s questionnaires) to all ‘eligible’<sup>10</sup> women and men personally, and do not use proxy respondents. Due to the sensitive nature of some of the topics covered (e.g. fertility preferences, family planning, domestic violence) DHS protocols specify that respondents (esp. husbands and wives) should be interviewed separately from each other and in private (ICF International 2012). This differs from LSMS-ISA surveys, which typically seek to interview the most knowledgeable household member for each plot or non-agricultural household enterprise but frequently resort to other household members as proxies (see Doss et al 2017 for self- vs. proxy response rates for LSMS-ISA surveys).<sup>11</sup> Asking individuals directly about their ownership rights over assets is generally assumed to best capture their personal perceptions and avoid biases from proxy respondents (Doss et al 2017). We hence rely on the DHS for the analysis of gender gaps in this paper.<sup>12</sup> Besides these advantages, it is important to acknowledge that there are dimensions of property ownership on which the DHS data cannot provide answers. First, the DHS data only capture the incidence of men and women owning any land and/or housing, and do not provide information on the monetary value of these assets. Second, ownership itself is a complicated context in societies shaped by legal pluralism and informal claims to property. As discussed in Schlager and Ostrom (1992), property rights can be described

> 9 The Liberia DHS includes the questions on housing, but not on land.

> 10 For most DHS, ‘eligible’ denotes all sampled men and women within a certain age range, typically 15-49 years (though some DHS chose wider age ranges for male respondents or only interview ever-married women). In our sample, the Kenya DHS uses a different eligibility criterion by fielding certain questions (including those on individual asset ownership) to a random sub-sample of households and respondents within households (KNBS et al 2015).

> 11 Interviewing multiple respondents per household often requires several visits to the household and increases the implementation cost of the household survey. This explains why most surveys solicit individual-level information for different household members from a single (proxy) respondent.

> 12 For those countries (Senegal, Zimbabwe) where data are available for more multiple years, we use the latest available survey. Because of the small number of countries with multiple surveys, we do not analyze changes in ownership over time.

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