the name of women grew faster post-reform than those registered to males. While increases in the number of registered mortgages (figure 8) were less pronounced, levelling off at 0.18 per block, the number of mortgages on jointly owned plots displayed a rapid increase.

Beyond exploring shifts in registration or changes in the properties of registered plots due to policy reform, administrative data also allow assessing the extent to which concerns about the evaluation design mentioned earlier may be relevant. Table 2 tabulates such data for the 2000-2019 period together with number and area of buildings in 2016 at block level for all of Maseru (column 1), and separately for areas identified as treatment (col. 3) or control (col. 4) and the rest of the city (col. 2). With a size of 62,500 m<sup>2</sup> of which 44% was privately held and registered in 2019, the average block includes about 28 registered plots of some 1,000 m<sup>2</sup> each titled using a sporadic (11) or systematic (17) process.

Beyond confirming trends noted earlier such as increases in the number of plots registered both sporadically and systematically and registered transfers and mortgages, table 2 shows pre-program differences between treatment (MMC 1-3) and control (MMC 27) that are relevant in two respects. First, a higher number of plots registered sporadically before the program in treatment than in control areas (6.23 vs. 0.33 in 2000 and 9.23 vs. 1.22 in 2010) suggests limited comparability between the two. Also, the number of sporadic registrations pre-program in wards MMC 1-3 (6.23 in 2000 and 9.23 in 2010) exceeds that in the remainder of Maseru (2.98 in 2000 and 5.73 in 2010), pointing towards limited representativeness of these areas for the intervention.<sup>12</sup> While interpreted imagery is available only for 2016 (i.e., post-intervention), it supports this argument by pointing towards a much higher number of structures or built-up area in the wards assigned to the treatment group (75 vs. 31 structures and 7,045 m<sup>2</sup> vs. 2,132 m<sup>2</sup> of built up area, respectively).

# **3.2 DID approach using household survey data and structures extracted from satellite imagery**

To provide data for a DID impact evaluation in the four wards (MMC 1-3 and 27) selected as treatment and control as described above, a baseline survey on a sample of 1,904 households was conducted in 2013 as described in more detail by Maredia et al. (2016), followed by an end-line survey in 2019, almost 6 years after the baseline. Both surveys used a household and female instrument and the endline survey instrument was identical to that used in the baseline except for minor modifications to improve response rates, capture changes in household composition and landownership, and provide detail on participation in the systematic registration program.

Baseline survey data as reported in data appendix table 1 indeed point towards significant differences in observed attributes between the groups. Propensity score matching (Rosenbaum and Rubin 1983)

> 12 Levels of systematic registration were similar between treatment and the rest of the intervention area and with an average of 0.5 plot registered systematically in the control, data suggest that contamination remained limited.

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