LSO_2019_LARIE_v01_M
Impact Evaluation of the Lesotho Land Administration Reform 2019
Name | Country code |
---|---|
Lesotho | LSO |
Other Household Survey [hh/oth]
Land Administration Reform Project (LARP) activities are under the Private Sector Development (PSD) Project of the Compact. LARP was implemented in Maseru and nearby areas in Lesotho between 2008 and 2013. MCC's compact 1 project aimed to support private sector development in several ways, including the registration of property rights to land through the Lesotho Land Administration Reform Project (LARP). Specifically, LARP had four sub-activities: (a) Policy and legal reform by which Technical assistance was made available to assess the legal and regulatory environment for land and adopt land policy and regulatory reforms that promote the use of land as collateral and an economic asset (b) Modernization and improvement of land administration services aimed at decreasing the time and inefficiencies associated with conducting a formal land transaction and increasing confidence in the formal system, thereby increasing demand for formal land registration services. (c) Systematic regularization of land in urban areas and improvement of rural land allocation processes aimed to simplify and streamline lease preparation and registration process through establishing a legal framework for systematic regularization and registration and provide secure land tenure in informal settlements in urban and peri-urban areas through issuing legal documents (referred to as “Lease”) to property owners. MCA hired Land Equity International (pilot activity) and COWI-Orgut (roll-out activity) to carry out the systematic land regularization work and the newly established Lesotho Land Administration Authority (LAA) Registration and Quality Unity (RQU) also carried out systematic regularization in rollout areas. (d) Public outreach and training supported land administration reform activities, including sensitization on LARP rollout and awareness raising on changes in land laws, the establishment of the LAA, women's land rights and conducting land transactions. The four sub-components of the LARP were considered fundamental to promote private sector development and stimulate economic growth. Specifically, they aimed at promoting the use of land as an economic asset by increasing tenure security and capitalization of land assets and ultimately reducing poverty through growth in real income.
Sample survey data [ssd]
Households, properties/parcels, individuals
Version 01: Edited, anonymous dataset for public distribution.
The survey covered the following topics:
The survey covered selected wards in Maseru city: MMC1, MMC2, MMC3 and MMC27
Name | Affiliation |
---|---|
Daniel Ali | World Bank Group |
Name |
---|
Millennium Challenge Corporation |
Complementing the baseline questionnaire, the endline questionnaire consists of over 20 sections with modules on:
Start | End | Cycle |
---|---|---|
2013-03 | 2013-06 | Baseline |
2019-01-11 | 2020-01-31 | Endline |
Name | Affiliation |
---|---|
Lesotho Bureau of Statistics | Ministry of Development Planning |
Endline Survey - Data collection by BOS - team comprised of 2 Survey Coordinators, 5 Supervisors team including three World Bank research team members. The role of the enumerators included pilot testing of the survey instruments and conducting the interview among potential and main respondents.
I) Primary Data Collection
Instruments: The endline survey revisited households that had been included in the 2013 baseline survey. The survey instruments (both from household head and women respondents) for the endline survey were the same as the baseline survey with slight modification to cover changes in the dynamics of household composition and landownership as well as participation in the land tenure regularization program.
Data were electronically collected using Survey Solutions deployed on a highly secure World Bank Cloud with geographic questions capable of capturing parcel boundaries using high resolution imagery as a basemap.
II) Secondary Data
The research team used:
As the survey was conducted through CAPI, the survey routing and many of the survey logic checks were automated and completed during fieldwork. This minimized the extent of data cleaning that was required during post-fieldwork.
The data cleaning process was done in multiple-stages. The first step was to ensure proper quality control during the fieldwork to ensure the accuracy of the final dataset. Errors that were caught at the fieldwork stage were corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the field to the head office of BOS where a second stage of data cleaning was undertaken. During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information of required variables, and sections. Any problems found were then reported back to the supervisors where the correction was then made. This was an ongoing process until all data were delivered to the head office.
After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete dataset. Problems that were identified in the process were reported to the supervisors for further corrections. The questionnaires were also checked for completeness and where necessary the relevant households were re-visited and a report sent back to the head office with the corrections.
The final stage of the cleaning process was to ensure that the household-and individual-level datasets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and any discrepancies were properly assessed and documented.
Is signing of a confidentiality declaration required? |
---|
yes |
Use of the dataset must be acknowledged using a citation which would include:
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | |
---|---|---|
Millennium Challenge Corporation | US Government | opendata@mcc.gov |
Daniel Ali | World Bank | dali1@worldbank.org |
DDI_LSO_2019_LARIE_v01_M
Name | Affiliation | Role |
---|---|---|
Development Economics Data Group | World Bank | Documentation of the survey |
2022-03-22
Version 01 (March 2022)
2022-03-22
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