# **4.3 Robustness check and incidence of measurement error**

To explore if limited representativeness and comparability of the areas chosen as treatment and control might explain differences in results between the DID approach and the block panel based on administrative data, we re-estimate (2) and (3) only for the 455 blocks in wards MMC 1, 2, 3 and 27 chosen for LARP impact evaluation. Results from these regressions are in panel B of tables 5, 6, and 7. While differences in the size of some coefficient estimates between restricted and full samples indeed imply that the wards chosen to evaluate LARP impact are not a good representation of Maseru overall, virtually all coefficient estimates for the restricted sample are still highly significant statistically, though in some cases slightly smaller intervention effects. It suggests that sample selection alone cannot explain the lack of significant results in the DID specification.

Several differences emerge. First, as to gender of registered owners (table 5 panel B) we find that (sporadic) registration of land plots in distant wards was more gender-biased than in the full sample; the point estimate for 1 is -0.50 in the restricted and -0.26 in the overall sample. Gender effects are broadly comparable to those in the unrestricted sample in terms of the likelihood of joint vs. male (0.34 vs. 0.37), female vs. male ββ (0.23 vs. 0.18), and joint vs. female (0.10 vs. 0.18) registration. Registration modalities display marked gender differences with sporadic registration favoring female sole owners (0.47) over joint ones (-0.35) and the opposite for systematic registration (-0.25 for female vs. male and 0.48 for joint vs. female). While the elimination of barriers to first-time registration 2) was estimated to have been more important than reduction of the transaction costs for registering mortgages 1) in the total sample, the opposite is (θθ true for the restricted sample (table 6); estimated coefficients on plots (sporadically) registered pre-2010 (θθ are larger than for those registered post-2010, in line with the notion that plots in outlying wards are less suitable as collateral. For registered land transfers (table 7), 2 1 is not significantly different from zero except for plots transferred by sole female owners. Point estimate for systematically registered plots (0.0014 θθ −θθ for mortgages and 0.0039 for land transfers) are of comparable magnitude to those for the entire sample.

We test if measurement error may bias results from the DID approach towards zero by comparing (accurate) registry data to responses obtained in the survey for the same households.<sup>16</sup> Spatially matching sampled plots for the household survey with the cadastral map (table 8) suggests that in 26% of cases information is reported incorrectly. Type I errors (survey respondents claiming to have lease document although nothing is present in the registry) and type II errors (respondents indicating lack of a legal land document in their household while a lease is registered in the registry) occur with approximately equal frequency. Both types

> 16 The proper way to eliminate discrepancies -and understand reasons for them- is to pre-populate the household survey with relevant information from administrative data. As digitization of registry data was carried out in parallel to household survey implementation, this was not possible here..

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