Project(2): SEED 2.0 the Scale Up (Baseline in Q1 2025, Intervention in May 2025)
Paul Gertler, Professor
Business, Haas School
Applications for Spring 2025 are closed for this project.
Passionated and interested in Field Experiments, Data collection, and applied econometrics?
Join an innovative and impactful research project evaluating a nationwide Randomized Controlled Trial (RCT) in Uganda involving 10,000 youth! This study explores the mode of delivery, content, and importance of digital skills within the Skills for Effective Entrepreneurship Development (SEED) program—a 3-week "mini-MBA" designed to empower youth with business and digital skills for lasting entrepreneurial success.
As a URAP [consider spelling out this acronym], you will support this exciting project and gain hands-on experience in:
- Field Experiments: Learn the design and implementation of large-scale RCTs testing innovative education and training interventions
- Data Collection: Support questionnaire development and manage data collection processes, including data entry, cleaning, organization, and quality assurance
- Research Supervision: Contribute to fieldwork monitoring, ensure adherence to research protocols, and assist in training field staff
- Data Analysis: Apply econometric methods to experimental data, develop data pipelines, and uncover meaningful insights
This is a unique opportunity to contribute to a project generating rigorous evidence on improving youth outcomes in education and entrepreneurship while addressing pressing global challenges.
Role: Students will:
Support the PI and Technical RA during RCT implementation
- Assist with data collection, including high-frequency checks and data quality assurance
- Prepare training materials for Field Officers and other field management staff
- Clean and analyze data using advanced methods beyond basic regression analysis, including machine learning for causal analysis
- Review literature on: Entrepreneurship, Youth skills training, Intra-household dynamics, Soft-skills measurement (task-based, biometric, and self-reported)
Qualifications: Technical Qualifications:
Previous experience in research and data analysis using Stata, R, or Python
Experience in handling and organizing large and complex datasets
Strong quantitative skills, including proficiency in data analysis software
Excellent communication and interpersonal skills for interacting with diverse stakeholders
Experience in field research, including survey design and data collection techniques
Understanding of development economics and randomized controlled trials (RCTs)
Excellent grades in advanced econometrics, statistics, and/or biostatistics required
Soft Skills:
Strong ability to anticipate, plan, prioritize, and meet deadlines
Capacity to handle multiple projects at once, effectively manage time, and interface confidently with co-workers
Self-motivated, detail-oriented, hard worker who enjoys working in teams
Desire to pursue graduate school in economics (and related fields), public policy, or data science a plus
Day-to-day supervisor for this project: Laura Chioda, Staff Researcher
Hours: 9-11 hrs
Social Sciences Engineering, Design & Technologies