{"type":"survey","doc_desc":{"title":"DDI-MCC-LSO-MSU-LARP-2013-v-1.1","idno":"DDI_LSO_2013_MCC-SRLUPUA_v01_M","producers":[{"name":"Millennium Challenge Corporation","abbreviation":"MCC","affiliation":"","role":"Metadata Producer"}],"prod_date":"2014-04-09","version_statement":{"version":"Version 1.1 (April 2014).  This version uses a new metadata template\nVersion 2.0 (April 2015). Edited version based on Version 01 (DDI-MCC-LSO-MSU-LARP-2013-v-1.1) that was done by Millennium Challenge Corporation.","version_notes":"National coverage"}},"study_desc":{"title_statement":{"idno":"LSO_2013_MCC-SRLUPUA_v01_M","title":"Systematic Regularization of Land in Urban and Peri-Urban Areas 2013","alt_title":"MCC-SRLUPUA 2013"},"authoring_entity":[{"name":"Michigan State University","affiliation":""}],"production_statement":{"funding_agencies":[{"name":"Millennium Challenge Corporation","abbreviation":"MCC","role":""},{"name":"Millennium Challenge Account Lesotho","abbreviation":"MCC-L","role":""}]},"distribution_statement":{"contact":[{"name":"Monitoring & Evaluation Division","affiliation":"Millennium Challenge Corporation","email":"impact-eval@mcc.gov","uri":""}]},"series_statement":{"series_name":"Independent Impact Evaluation"},"version_statement":{"version":"Anonymized dataset for public distribution"},"study_info":{"keywords":[{"keyword":"legal reform","uri":"","vocab":""},{"keyword":"credit","uri":"","vocab":""},{"keyword":"debit","uri":"","vocab":""},{"keyword":"land regularization","uri":"","vocab":""}],"abstract":"Michigan State University was assigned to design the impact evaluation (IE) of the Land Administration Reform Project (LARP) funded under the Millennium Challenge Account (MCA)-Lesotho compact. The impact evaluation is designed to test the following key economic hypotheses. It is hypothesized that land with formally recognized titles will result in:\n1. Increased number of land parcels used as collateral for mortgage\n2. Increased investment in the property, increased frequency of transfers, subletting, rentals, and other economic activities\n3. Increased value of land\n4. Reduction in land related conflicts\n5. Increase in income\/expenditures of beneficiaries\n\nThe purpose of the rigorous IE design is to measure and monitor these hypothesized impacts and assess the causality in effects outlined in the impact pathway. The IE design is based on a difference-in-difference (DiD) analytical framework requiring the collection and analysis of baseline and end line data from treatment and control areas. Data towards the baseline assessment were collected by T&T Geomatics and MASAZI Development Associates (referred hereafter as the \u2018survey firm\u2019) from March to June 2013 and final data sets and data documentation were submitted to MCA on September 27, 2013. This documentation describes the variables created by Michigan State University based on the data files submitted by the survey firm to generate variables used for descriptive data analysis reflected in the Baseline Report. The explanation of how variables are generated based on original data is found in the difinition of the variable in the variable list. \"Missing\" values reported in the variable list correspond to \"no response\", \"don't know\" or \"not applicable\" in the original data files. The original data had duplicated observation and other issues. How these issues were addressed is described in Annex A, which is included as a separate attachment to this meta data.","coll_dates":[{"start":"2013-03","end":"2013-06","cycle":"Baseline"}],"nation":[{"name":"Lesotho","abbreviation":"LSO"}],"geog_coverage":"The survey covered the following village\/sub-villages in MMC1, MMC2, MMC3 and MMC27 in Maseru city:\n\nMMC # Village name Group Name of the cluster (sub-village) Cluster code\n\nMMC01 Boiketlo Treatment Boiketlo 101\nMMC01 Kuroane Treatment Kuroane 102\nMMC01 Le-coop Treatment Le-coop 103\nMMC01 Pecha Treatment Pecha 104\nMMC01 Phomolong Treatment Phomolong 1 105\nMMC01 Phomolong Treatment Phomolong 2 106\nMMC01 Rasetimala Treatment Rasetimela 1 107\nMMC01 Rasetimala Treatment Rasetimela 2 108\nMMC01 Selakhapane Treatment Selakhapane 109\nMMC01 Thoteng-Khubetsoana Treatment Thoteng-Khubetsoana 110\nMMC01 Bochabela I Treatment Bochabela I 111\nMMC01 Bochabela I Treatment Bochabela II 112\nMMC01 Bochabela II Treatment Bochabela III 113\nMMC02 Bochabela IV Treatment Bochabela IV 201\nMMC02 Lifelekoaneng-Mabote Treatment Lifelekoaneng-Mabote 202\nMMC02 Mapaleng-Mabote Treatment Mapaleng-Mabote 203\nMMC02 Maqalika Treatment Maqalika 204\nMMC02 Phahameng-Khubetsoana Treatment Phahameng-Khubetsoana 205\nMMC02 Phpoletsa-Mabote Treatment Phpoletsa-Mabote 206\nMMC02 Rural Treatment Rural 207\nMMC02 Sebaboleng Treatment Sebaboleng 208\nMMC02 Taung-Mabote Treatment Taung Mabote 209\nMMC02 Thoteng-Mabote Treatment Thoteng-Mabote 1 210\nMMC02 Thoteng-Mabote Treatment Thoteng-Mabote 2 211\nMMC03 Tsosane (part not regularized) Treatment Tsosane (not reg) 1 301\nMMC03 Tsosane (part not regularized) Treatment Tsosane (not reg) 2 302\nMMC03 Naleli-Tsosane Treatment Naleli-Tsosane 1 303\nMMC03 Naleli-Tsosane Treatment Naleli-Tsosane 2 304\nMMC27 Ha Foso Control Ha Foso 1 2701\nMMC27 Ha Foso Control Ha Foso 2 2702\nMMC27 Ikheteleng Control Ikhetelong 1 2703\nMMC27 Ikheteleng Control Ikhetelong 2 2704\nMMC27 Ikheteleng Control Ikhetelong 3 2705\nMMC27 Khopane Control Khopane 2706\nMMC27 Koalabata Control Koalabata 1 2707\nMMC27 Koalabata Control Koalabata 2 2708\nMMC27 Koalabata Control Koalabata 3 2709\nMMC27 Koalabata Control Koalabata 4 2710\nMMC27 Marabeng Control Marabeng 2711\nMMC27 Sekhutlong Control Sekhutlong 2712","analysis_unit":"Households","universe":"Households in the 22 treatment villages","data_kind":"Sample survey data [ssd]"},"method":{"data_collection":{"data_collectors":[{"name":"T&T Geomatics","abbreviation":"","affiliation":""},{"name":"MASAZI Development Associates","abbreviation":"","affiliation":""}],"sampling_procedure":"In the first step, the 22 treatment villages identified were divided into 28 clusters (or sub-villages) and the 6 control villages were divided into 12 clusters (or sub-villages) such that each cluster had at least 100 households and belonged to only one village. In other words, big villages were sub-divided into smaller clusters (or sub-villages) for sampling purpose. Each of these villages or sub-villages were considered as units of intervention for the IE design (and statistics analysis). Based on the village boundaries identified in the field (with the help from the LARP Project Implementing Unit), and using the GPS coordinates of this boundary and superimposing it on the satellite imagery of the MMC map that shows the density of land parcels with structures (i.e., roof outlines), the 40 sub-villages were mapped.\n\nIn step two, 45 households from each cluster were randomly selected. To aid in this selection process, a GIS based method of 'listing' was undertaken. This involved using orthophotos to pre-vectorize land parcels (which were provided by COWI, the project implementer) and using them to produce GIS maps for sample selection. This method was used to randomly select the required numbers of households (and replacement households) in each cluster across all MMCs.\n\nIn step three, to augment the number of parcels in the survey that are used for commercial purposes, a field based listing exercise was undertaken to identify all the parcels in each cluster where some kind of commercial activities would be taking place. An average of about 4-6 additional parcels per cluster that were identified as commercial plots (but were not part of the sample selection based on the GIS method) were randomly selected to increase the number of observations for commercial parcels.\n\nFor the purpose of this IE, in both steps 2 and 3 of sample selection, the sampling frame was defined as \"households that have land parcels that belong to them in the same village where they are being interviewed, and for which they have not yet obtained any Lease. The land parcel could be either occupied by the HH or rented to others for housing or commercial purpose.\" However, as reported in the results section, 276 parcels inventoried using the GIS based sampling frame already had Lease. To establish the baseline, parcels with a Lease are excluded from all the plot level analysis included in the baseline report.","research_instrument":"The questionnaire included more than 25 sections encompassing modules on:\n\u00b7 Household characteristics (demographic information by each member of the HH)\n\u00b7 Employment and sources of any other cash transfers\n\u00b7 Identification and list of all the parcels\n\u00b7 Information on Parcel Acquisition, Documents and Land Value\n\u00b7 Land conflicts\n\u00b7 Rights to the land and perceptions of the risk\n\u00b7 Parcels rented out, rented in\n\u00b7 Characteristics of parcels\n\u00b7 Investments on land\n\u00b7 Perceptions about Lease, renting land, the land law, women's rights and LAA\n\u00b7 Ownership of Assets\n\u00b7 Expenditures\n\u00b7 Credit in the last 12 months\n\u00b7 Consumption\n\u00b7 Woman module","coll_situation":"The evaluation is based on household level surveys that included interviewing the head of the household based on a detailed instrument which was translated into Sesotho. The survey has detailed sections for each of the outcomes to be evaluated, both intermediate and final outcomes, and some monitoring and evaluation (M&E) indicators to be monitored.\n\nThe questionnaire included more than 25 sections encompassing modules on:\n\u00b7 Household characteristics (demographic information by each member of the HH)\n\u00b7 Employment and sources of any other cash transfers\n\u00b7 Identification and list of all the parcels\n\u00b7 Information on Parcel Acquisition, Documents and Land Value\n\u00b7 Land conflicts\n\u00b7 Rights to the land and perceptions of the risk\n\u00b7 Parcels rented out, rented in\n\u00b7 Characteristics of parcels\n\u00b7 Investments on land\n\u00b7 Perceptions about Lease, renting land, the land law, women's rights and LAA\n\u00b7 Ownership of Assets\n\u00b7 Expenditures\n\u00b7 Credit in the last 12 months\n\u00b7 Consumption\n\u00b7 Woman module\n\nIn addition, each of the survey households was geo-referenced for ease of locating the household for a follow-up survey. A separate module targeted towards women was administered separately with the women head of the family. The survey was translated and administered in Sesotho, and was designed to take between 1 \u00bd to 2 hours to complete. Copies of the survey instruments are available upon request.\n\nThe baseline survey was implemented in the selected villages from March to June 2013. The number of households surveyed in treatment and control MMCs across all the clusters was 1826. However, the data set that MSU received has many gaps and non-responses to several questions. Thus the number of observations on which a specific estimate is based varies across Tables included in the Baseline Report.","weight":"The sample weight variable used in the baseline report analysis was created by the survey firm and sourced from the original data file. Sampling weights were computed in order to adjust for the overall sample figures in relation to the population scale, to correct imbalances in sampling ratios from one group to another due to non-response in the samples. The weights were calculated as a factor of the population per cluster (Ni) and the sample size (ni) per cluster i.e Ni\/ni where i is the ith cluster."}},"data_access":{"dataset_availability":{"access_place":"Millennium Challenge Corporation","access_place_uri":"http:\/\/data.mcc.gov\/evaluations\/index.php\/catalog\/85","original_archive":"Millennium Challenge Corporation\nhttp:\/\/data.mcc.gov\/evaluations\/index.php\/catalog\/85\nCost: None"},"dataset_use":{"conf_dec":[{"txt":"","required":"no","form_no":"","uri":""}],"cit_req":"The use of the datasets must be acknowledged using a citation which would include:\n- the identification of the Primary Investigator (including country name);\n- the full title of the survey and its acronym (when available), and the year(s) of implementation;\n- the survey reference number;\n- the source and date of download (for datasets disseminated online).\n\nExample:\n\nMichigan State University. Lesotho Systematic Regularization of Land in Urban and Peri-Urban Areas (MCC-SRLUPUA) 2013, Ref. LSO_2013_MCC-SRLUPUA_v01_M. Dataset downloaded from [URL] on [date].","disclaimer":"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."}}},"data_files":[],"variables":[],"variable_groups":[]}