start and end dates for more than 98 percent of registered sales and mortgages based on actual transactions rather than expert opinions about “typical” transactions.

To create spatial units as a basis for impact evaluation, we divide the area of Maseru Municipal Corporation (MMC) into a grid of 250m x 250m blocks and aggregate spatial variables for each block. Figure A1 in the Appendix<sup>6</sup> illustrates the principle: block boundaries are represented by a dashed line and parcels are assigned colors depending on whether they were registered sporadically before (purple) or after (brown) the 2010 legal changes or systematically after 2010 (blue). Spaces the rights to which are not registered in the name of a private individual or legal entity remain white and 2016 building footprints, derived from high-resolution satellite imagery using machine learning, are displayed for illustrative purposes.<sup>7</sup> Figure 1 maps the MMC area: the 722 blocks not covered by systematic initial registration are colored white and the 1,210 blocks covered by systematic first registration are colored based on whether they entered LARP through the 2011 pilot (light grey; 150 blocks); the initial roll-out in 2012 (dark grey; 29 blocks) or the full roll-out in 2013 (black; 1,031 blocks). Relevant outcomes from the registry (e.g., number of registered parcels, land sales and mortgage transactions) are then aggregated to the block level on an annual basis so that blocks serve as the basis of econometric analysis.

We complement that data with gridded information on built area and population on each block to control for time-varying attributes. Public data from the World Settlement Footprint Evolution (WSFE) annual time series on built area for the period 1985–2015 at 30x30m resolution was complemented with a layer on built area in 2019 at 10 m resolution made available by the WSFE team.<sup>8</sup> In the absence of time series 3D data on built volume, we also use this variable as a proxy for land-related investment in durable structures by overlaying it with the registered parcel layer to provide an estimate of built area on registered and nonregistered parcels for each block. Population data for 2000–19 is from the Center for International Earth Science Information Network (CIESIN) gridded population of the world (version 4) data set at a 1 km spatial and 5-year temporal resolution. It is used similarly throughout to generate annual values of block population density to serve as a control.

# **3.2 Descriptive Statistics**

Table 1 summarizes transaction-level variables for the 39-year period (1981–2019) for which data is available (column 1) and the 1981–2009 pre-reform period split into pre-and post-2000 (columns 2 and 3);

> 6 Figures and tables whose number is preceded by an A are all in the Appendix.

> 7 Parcels that cross block boundaries are assigned to the block containing the parcel centroid.

> 8 Annual time series data from 1985 to 2015 is available from <u><mark>https://doi.org/10.6084/m9.figshare.10048412.v1;</mark> data at 10m resolution for 2019</u> was kindly made available by M. Marconcini and missing annual values (2016–18) interpolated using a cubic spline. Results in Tables 3 and 4 are based on pre-2015 values and thus robust. Differences in resolution and the methodology used to compute built area between the 1985–2015 series and the 2019 values reduce the consistency of the time series so that results in table 5 should be considered only illustrative.

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