Project 1: Advanced Research Support for Hard and Soft Skills for Youth Entrepreneurship in Uganda, Two RCTs.
Paul Gertler, Professor
Business, Haas School
Applications for Spring 2024 are closed for this project.
*** Project 1: Hard and Soft Entrepreneurship Skills for youth in Uganda, Two RCTs ***
We study the medium and long term impacts (4y and 9y) of two exciting youth entrepreneurship programs. and innovative youth skill-development and entrepreneurship interventions (Skills for Effective Entrepreneurship Development, SEED, and the Educate! Experience) were implemented at scale in Uganda to study the impacts of three curricula that featured different combinations/intensities of soft and hard skills: SEED-hard (25% focus on soft skills), SEED-soft (75% focus on soft skills) and Educate! (~90% devoted to soft skills). The soft skills component at the core of the SEED and Educate! interventions was developed and implemented by the Educate! NGO.
The two studies involve over 6,000 Ugandan young adults in their mid-20s (50% female and 80-90% in a relationship), covering well over 3,000 businesses. This work is unique in its use of data collected at multiple points in time (baseline, 4-year follow-up, 9-year follow-up), which enables us to study the trajectory of impacts and skill development over time.
We measure not only impacts on traditional economic outcomes (earnings, business creation, labor market outcomes etc), but we also study the social spillovers of these two interventions on family formation, mental health, skills, and other social well-being.
Furthermore, with exciting and novel data on hand, we are poised to answer some of the following questions:
- Can we improve youth's ability to negotiate?
- What makes a good negotiator?
- Which tactics are more successful (e.g., split the difference, win-win arguments, cheap talk, aggressive bidding, etc)? What is the role of fairness in shaping outcomes?
- Which personality skills matter (e.g., inter- and intra-personal skills)?
Data to answer these questions are generated in the context of a lab-in-the-field experiment with real stakes (a Negotiation Task). We have access to a rich data set, including recordings and transcripts for several rounds of negotiation for a large sample of youth.
This is an exciting project that touches upon different strands of the economic and methodological literatures including behavioral economics, negotiations, Randomized Control Trials, Causal Inference and machine learning methods and other novel statistical and econometric techniques.
Role: *** Project 1: Hard and Soft Skills for Youth Entrepreneurship in Uganda, Two RCTs ***
Roles: Students who work on this project will receive training on best practices in primary data collection, data analysis and causal impact , conducting literature reviews, and advanced econometrics.
- Clean and analyze data
- Causal Analysis beyond simple regression analysis, students should be familiar Machine Learning for causal analysis and other advanced methods
- Review literature on entrepreneurship, youth skill training, intra-household dynamics, soft-skills measurements (task based, biometrics, self reported) and negotiation
- Support during questionnaire development, if necessary
Qualifications:
- Advanced Data analysis using Stata, R, and/or Python
- Strong written and oral communication skills
- Highly proficiency in Big Data and Machine Learning Methods, machine learning methods for causal inference
-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
- Excellent grades in advanced econometrics, statistics, and/or biostatistics required.
Qualifications: Qualifications:
- *Advanced* Data analysis using Stata, R, or Python
- *Advanced* experience in handling and organizing large and complex data sets
- Strong written and oral communication skills
- Highly proficiency in Big Data and Machine Learning Methods, machine learning methods for causal inference
-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
- Excellent grades in advanced econometrics, statistics, and/or biostatistics required.
Day-to-day supervisor for this project: Laura Chioda (Director of Research), Staff Researcher
Hours: 9-11 hrs
Related website: http://www.paulgertler.com/
Social Sciences Engineering, Design & Technologies