Our Data
GLD Data provides rich datasets on governance and local development, covering topics like elections, service provision, and gender equality across the Middle East, North Africa, and Sub-Saharan Africa. You can access public datasets on Harvard Dataverse or request embargoed data via our Data Use Agreement. You can also request survey support from GLD Data, we provide services like questionnaire design, data cleaning, and dissemination. Learn more and access tools to estimate survey costs further down on this page!
Available Data
GLD has a rich set of data on issues relating to governance and local development from countries in the Middle East, North Africa, and Sub-Saharan Africa. Our goal is always for our datasets to be available and used by those who work on similar topics.
Data currently available:
| The Local Governance Performance Index (LGPI) Household Survey 2015: Tunisia | |
| Year | 2015 |
| Countries | Tunisia |
| Topics | This dataset examines individuals' perceptions and experiences of governance and service provision. It enables analysis of different governance dimensions, including authority, service delivery, and local development. |
| Unique Variables | 1059 |
| Sample Size | 3657 |
| Access Link | https://doi.org/10.7910/DVN/HH0SBH |
| The Local Governance Performance Index (LGPI) Household Survey 2016: Malawi | |
| Year | 2016 |
| Countries | Malawi |
| Topics | This dataset examines individuals' perceptions and experiences of governance and service delivery across sectors such as health, education, security, and administrative services. It highlights variations in governance and service provision across communities and social groups. |
| Unique Variables | 2374 |
| Sample Size | 8060 |
| Access Link | https://doi.org/10.7910/DVN/IURPRI |
| The Local Governance Performance Index (LGPI) Household Survey 2019: Kenya, Malawi, Zambia | |
| Year | 2019 |
| Countries | Kenya, Malawi, Zambia |
| Topics | This dataset covers individual- and community-level governance, examining perceptions and experiences related to participation, service provision, security, social norms, welfare, and demographics. It enables analysis of different governance dimensions, including authority, corruption, extraction, participation, and transparency. |
| Unique Variables | 29641 |
| Sample Size | 23954 |
| Access Link | https://doi.org/10.7910/DVN/PJKXL1 |
| GLD-IPOR Malawi Covid Panel Survey | |
| Year | 2020 |
| Countries | Malawi |
| Topics | This dataset covers pandemic responses and crisis resilience, examining how Covid-19 affected individuals and communities. It examines citizens' knowledge, attitudes, fears, vulnerabilities, social distancing practices, and concerns about enforcement, stigma, and the role of authorities. |
| Unique Variables | 1723 |
| Sample Size | 8703 |
| Access Link | https://doi.org/10.7910/DVN/MOOI8X |
| Zambia Election Panel Survey Dataset (ZEPS) | |
| Year | 2021 |
| Countries | Zambia |
| Topics | This dataset explores electoral processes by examining voter perceptions and behavior in the 2021 election, including issues related to election quality and election-related violence. It explores how citizens form political preferences and voting choices, including shifts in political support. |
| Unique Variables | 406 |
| Sample Size | 4445 |
| Access Link | https://doi.org/10.7910/DVN/VGFQZI |
| GLD-SAIPAR Covid-19 Survey in Zambia | |
| Year | 2020-2021 |
| Countries | Zambia |
| Topics | This dataset covers pandemic responses and crisis resilience, examining how Covid-19 affected individuals and communities. It exaimes citizens' knowledge, attitudes, fears, vulnerabilities, social distancing practices, and concerns about enforcement, stigma, and the role of authorities. |
| Unique Variables | 869 |
| Sample Size | 2903 |
| Access Link | https://doi.org/10.7910/DVN/JIKM9F |
| GLD Malawi Member of Parliament Survey Dataset | |
| Year | 2021-2022 |
| Countries | Malawi |
| Topics | This dataset examines the factors that influence members of parliament's (MPs) decisions to run for office. It explores the role of political parties and ethnic and religious communities in shaping candidates' bids for office. |
| Unique Variables | 72 |
| Sample Size | 137 |
| Access Link | https://doi.org/10.7910/DVN/D8MTMW |
Replication Data Available:
| Replication Data for: Generative AI as a Safety Net for Survey Question Refinement | |
| Year | 2025 |
| Countries | N/A |
| Topics | The dataset addresses the use of AI in survey methodology by examining outputs from a generative AI experiment in which ChatGPT was applied to survey questions to evaluate potential design, interpretation, and contextual issues. The dataset includes AI-generated responses and structured qualititative coding used to analyze patterns in the model's feedback. |
| Unique Variables | N/A |
| Overall Sample Size | N/A |
| Access Link | https://doi.org/10.7910/DVN/AN3U9F |
| Replication Data for: Exploring Generative AI's Role in Preparing Surveys for Translation | |
| Year | 2023 |
| Countries | N/A |
| Topics | The dataset addresses the use of AI in survey methodology by examining output from a generative AI experiment in which ChatGPT was applied to survey questions to identify linguistic and cultural features that may pose challenges for translation. The dataset includes both the AI-generated responses and qualitative coding of these outputs. |
| Unique Variables | N/A |
| Overall Sample Size | N/A |
| Access Link | https://doi.org/10.7910/DVN/HFT8TD |
| Replication Data for: Identity, Information, and Voting: Lessons on African Elections from a Survey Experiment | |
| Year | 2023 |
| Countries | Zambia, Malawi, Kenya |
| Topics | The dataset addresses electoral processes by examining how candidate ethnicity shapes voter preferences in elections. The dataset explores voters' expectations regarding distributional favoritism, candidate quality, and accessibility. |
| Unique Variables | 110 |
| Overall Sample Size | 19202 |
| Access Link | https://doi.org/10.7910/DVN/M6XKDA |
How to Access GLD Data
All of GLD's available datasets can be found in the Harvard Dataverse. If you have any questions about the available data or data that is not yet available, please contact data@gld.gu.se.
Interactive View and Data Download
Our interactive ShinyApp tool makes it easy to explore, download, and customize the LGPI 2019 dataset—perfect for researchers, students, and policymakers. The dataset is built from a household survey conducted in Kenya, Malawi, and Zambia, offering insights into governance at both individual and community levels.
The data covers a wide range of topics, including:
- Participation (e.g., community meetings, voting)
- Service Provision (e.g., education, health, water, electricity)
- Security (e.g., crime, dispute resolution)
- Social Norms (e.g., social obligations, sanctioning)
- Welfare & Demographics (e.g., land access, food security, shelter)
With the ShinyApp, you can sort the data by region or topic, tailoring it to your specific interests. Whether you're curious about education in Zambia or voting patterns in Kenya, this tool makes the data accessible and actionable.
View the LGPI 2019 Dataset here!
What is a ShinyApp?
A ShinyApp is an interactive web application built using the Shiny framework in R, a programming language for statistical computing and graphics. Shiny is developed by RStudio (now Posit) and enables R users to create dynamic, web-based applications directly from R scripts without requiring extensive web development skills.
Data Support Services
GLD Data is happy to offer cost-effective support for the collection, management, analysis, and dissemination of survey data. We have experience with surveys implemented online, face-to-face, and via the telephone across a wide range of contexts.
Our full list of services include:
- Questionnaire Design
- Sampling Strategies
- Translation Facilitation
- Survey Coding
- Enumerator Training Materials
- Data Quality Monitoring
- Data Cleaning
- Documentation
- Dissemination
Get Survey Support
Are you interested in survey support? You can schedule a 1-hour consultation by sending an email to data@gld.gu.se and can get a preliminary cost estimate using our online survey support cost calculator: gld-data.shinyapps.io/Survey_Collaboration_Budget/