Impact evaluation of the Improvement of Land Governance in Uganda to Increase Productivity of Small-Scale Farmers on Mailo-Land 2023
Endline
Uganda, 2023
Get MicrodataIdentification
UGA_2023_ILGUIE-EL_v01_M
Impact evaluation of the Improvement of Land Governance in Uganda to Increase Productivity of Small-Scale Farmers on Mailo-Land 2023
Endline
ILGUIE-EL 2023
| Name | Country code |
|---|---|
| Uganda | UGA |
1-2-3 Survey, phase 3 [hh/123-3]
An endline data collection took place in 2023 to assess the impact of the GIZ supported pilot program to test approaches for systematic demarcation and adjudication of Mailo land occupied by tenants in the form of land inventories in 8 sub-counties in Mityana and Mubende districts of Uganda. The proposed impact evaluation of the delivery of land inventories to Mailo land will investigate the impact of the program on perceived tenure security, land-related investment by smallholders, access to credit and agricultural productivity.
The overlap of ownership and use rights on mailo land has been identified as a key impediment to investment and improved productive efficiency in Uganda’s agricultural economy. Previous studies have shown that mailo “occupancy rights convey significantly lower incentives to invest in trees, soil conservation, and manure application than full ownership.
To address the issue of securing rights of mailo tenants in a way that can increase the level of investment by smallholders, access to credit and boost agricultural productivity, the German Agency for International Development (GIZ) developed a pilot program to test approaches for systematic demarcation and adjudication of mailo land occupied by tenants in the form of land inventories in 8 sub-counties in Mityana and Mubende districts.
Study Objectives
The impact evaluation of the delivery of land inventories to mailo land tenants will serves multiple objectives:
a) Gain better understanding of the impacts of strengthening tenants’ rights in Mityana and Mubende districts. Findings are to provide critical information necessary to understand and quantify both expected impacts and risks associated with the program. Results are to be disaggregated by gender.
b) Identify best practices as well as potential issues in the implementation process and provide recommendations to inform the design of a subsequent national roll-out to cover mailo land but also similar tenure arrangements in Uganda such as Native Freeholds and Church’s land.
c) Evaluation of the complementary intervention aimed at converting land inventories into certificates of occupancy (CoO)/mailo title will help identify the best incentives for registration of CoO/mailo title as well as the benefits associated to registration vs. demarcation on key outcome variables (investment, land management, agricultural productivity).
d) Inform potential new donors’ engagement in support to the implementation of the National Land Policy’s strategic objectives.
Sample survey data [ssd]
Household and individual
Version
Version 01: Edited, anonymized dataset for public distribution.
Scope
The survey covered the following topics:
• Wage employment and non-market labor
• Housing conditions, water, and sanitation
• Sources of income, financial decision making, savings, credit, borrowing, and banking in the past 12 months
• Parcel management and use
• Tenure and documentation
• Conflict and perception of tenure security
• Plot management
• Crops
• Certificate of occupancy interest/value
• Purchase land
• Gender, awareness, and legal knowledge
• Credit
• Non crop farming household enterprises/activities
• Shocks and coping strategies
• Welfare and food security
• Decision making, bargaining, and social capital
• Household assets
• Animal assets
• Livelihood and assets
Producers and sponsors
| Name | Affiliation |
|---|---|
| Heather Huntington | Cloudburst Group |
| Thea Hilhorst | World Bank |
| Kate Marple-Cantrell | Cloudburst Group |
| Klaus Deininger | World Bank |
| Daniel Ayalew Ali | World Bank |
| Name | Abbreviation | Role |
|---|---|---|
| Gesellschaft fuer Internationale Zusammenarbeit | GIZ | Funding |
Sampling
Endline data collection took place in 2023. Wilsken Agencies LTD, a Ugandan research firm, conducted the endline data collection. An intensive 18-day-long interviewer training workshop for 60 interviewers was conducted between July 15 and August 10, 2023. Feedback from training allowed the team to improve the instruments and further adapt them to the local context before data collection.
Following training, a survey pre-test took place over two days beginning August 7, 2023 in four villages in Mityana District to give all team members direct experience using the survey instrument. The data collected from this pre-test also led to several minor improvements in the survey instrument.
In line with the requirements for human subject protection, the research team received approval from the Mildmay Research Ethics Committee Institutional Review Board on May 16, 2023. Verbal informed consent was received from each participant after reading a statement about the purpose of the research, the content of the survey, any risks or benefits, and the time commitment.
Tenant survey endline data collection took place from August 17 to September 30, 2023. The interviews with landlords commenced on Tuesday, September 19, 2023 and ended on October 26, 2023.
At endline, 1,593 tenant interviews were completed, representing a total attrition rate for the tenant survey of 37 percent from the baseline sample of 2,534 respondents. Attired baseline respondents were not replaced. The primary causes of attrition were household relocation to another area and refusals. Additional details are provided in the sections below. For the landlord survey, the data collection team was able to track and interview 179 respondents, representing about one-third of the unique landlord names collected in the study area.
At endline, 1,593 tenant interviews were completed, representing a total attrition rate for the tenant survey of 37 percent from the baseline sample of 2,534 respondents.
Survey instrument
The endline survey utilized three questionnaires: household, agriculture, and landlord. The questionnaires include the following sections:
Section A - Baseline Household Identification
Section B - Household Roster
Section C - Wage Employment and Non-Market Labor Activities
Section D - Housing Conditions, Water, and Sanitation
Section E - Sources of Income, Financial Decision Making, Savings, Credit, Borrowing and Banking
Section F - Parcel Management and Use
Section G - Tenure and Documentation
Section H - Conflict and Perception of Tenure Security
Section I - Plot Management
Section J - Crops
Section K - Certificate of Occupancy Interest/Value
Section L - Purchase Land
Section M - Gender Perceptions, Legal Knowledge and Conflicts
Section N - Credit
Section O - Non-Crop Farming Household Enterprise/Activities
Section P - Shocks and Coping Strategies
Section Q - Welfare and Food Security
Section R - Decision Making, Bargaining and Social Capital
Section S - Household Assets
Section T - Animal Assets
Section U - Livelihood Assets
The endline data collection effort utilized the following quality control measures: observation of interviewers by team leaders, daily quality control checks by the research team, and auditing/re-interviewing of respondents. Team leaders and quality control supervisors often accompanied interviewers and sat in for part or all of their interviews. For team leaders, this happened at least once every day for one interviewee, and the supervisors accompanied two to three enumerators each time they accompanied a team of enumerators. The selection of the interviewers to observe was informed by the results of the audits and high-frequency checks. Audits occurred on 12 percent of surveys. The audit data was compared to the original data by the research team and the number of discrepancies were recorded. If a large number of discrepancies were found, additional training was offered to the enumerator. If necessary, additional targeted audits were used to investigate unusual patterns that could indicate data falsification.
Finally, the most thorough checks were remote high-frequency checks conducted by the research team on 100 percent of all tenant surveys using SurveyCTO, the results of which the team compiled and shared with the survey firm. The high-frequency checks compared survey responses by each enumerator to search for patterns indicating data falsification or systematic errors that should be corrected, including short survey times, missing responses, a low average number of "other, specify" responses or multiple selections, and any other significant irregularities by day, geography, team, or interviewer.
Data collection
| Start | End |
|---|---|
| 2023-07-15 | 2023-10-26 |
- Computer Assisted Personal Interview [capi]
Prior to starting data collection, field staff were trained for a period of approximately two weeks with practical sessions to introduce the concept of CAPI (Computer Assisted Personal Interviews) using survey solutions.
The field teams comprised of a driver, a supervisor, and four enumerators. Each enumerator had a tablet and each supervisor had either a tablet or a computer (laptop). All data was captured directly on tablets using SurveyCTO. The data collected was electronically sent to the research team daily.
As the survey was conducted through CAPI, the survey routing and many of the survey logic checks were automated and completed during fieldwork.
Field work started on the 15th of July 2023 and ended on the 26th of October 2023.
Data Access
Heather Huntington (University of Pennsylvania), Kate Marple-Cantrell (The Cloudburst Group), and Daniel Ali Ayalew and Thea Hilhorst from the World Bank. Endline: Impact evaluation of the Improvement of Land Governance in Uganda to Increase Productivity of Small-Scale Farmers on Mailo-Land (ILGU) 2023. Ref: UGA_2023_ILGUIE-EL_v01_M. Dataset downloaded from [url] on [date].
Disclaimer and copyrights
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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Daniel Ayalew Ali | World Bank | dali1@worldbank.org |
Metadata production
DDI_UGA_2023_ILGUIE-EL_v01_M
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the survey |
2025-04-30
Metadata version
Version 01 (April 2025)