Course Modules:

Module 1: Overview of Economic Data Sources

• Surveys vs. administrative data
• Censuses, registers, and big data
• Institutional sources and metadata
• Case Study: Integrating administrative tax data in East Africa

Module 2: Survey Design and Data Collection

• Sampling strategies for economic surveys
• Questionnaire design for businesses and households
• Handling non-response and bias
• Case Study: Kenya Integrated Household Budget Survey (KIHBS)

Module 3: Administrative Data for Economic Statistics

• Revenue records, social security, customs, and VAT
• Data-sharing protocols and agreements
• Legal and privacy considerations
• Case Study: Use of customs data in trade statistics

Module 4: Estimation Techniques I – Missing Data

• Imputation techniques (mean, regression-based)
• Handling non-sampling errors
• Adjusting for outliers and extreme values
• Case Study: Estimating missing values in business register surveys

Module 5: Estimation Techniques II – Forecasting and Trends

• Interpolation and extrapolation basics
• Time series models for small datasets
• Nowcasting and early estimates
• Case Study: GDP forecasting with partial data

Module 6: Benchmarking and Reconciliation

• Combining sources for consistent estimates
• Benchmarking against macroeconomic aggregates
• Cross-sector reconciliation techniques
• Case Study: Data reconciliation in national income statistics

Module 7: Sector-Specific Estimation Approaches

• Informal sector measurement
• Estimating shadow economy and underreporting
• Adjustments in agriculture and services
• Case Study: Informal sector contribution in Sub-Saharan Africa

Module 8: Statistical Software and Tools

• Excel, R, STATA for economic estimation
• Data validation and cleaning tools
• Interactive dashboards for data reporting
• Case Study: Using STATA to model price indices

Module 9: Data Quality Assessment Frameworks

• Accuracy, reliability, timeliness, comparability
• International best practices (IMF DQAF, UN NQAF)
• Practical data quality audits
• Case Study: Quality assurance in Uganda Bureau of Statistics

Module 10: Applied Group Exercise and Presentations

• Team-based data analysis project
• Applying estimation methods to simulated data
• Presentation and peer review
• Case Study: Simulated national account estimation challenge