2021-22 "Understanding and Predicting Income-Generating Electricity Use in India"
The Stanford King Center on Global Development’s Academic Year Part-Time Research Assistant Program connects King Center faculty affiliates and affiliated researchers with undergraduate and master's students committed to providing research support for up to 15 hours per week during fall, winter, and spring quarters.
Students have the opportunity to engage in world-class research and have real-world impact. Undergraduate student research assistants earn $17.50 per hour and master's student research assistants earn $25 per hour. Research assistants can work a maximum of 15 hours per week. Students must be enrolled full-time to participate.
RESEARCH PROJECT DESCRIPTION:
Energy access and use is directly linked to changes in income generation and productivity. The Indian government has tracked the financial activities of over 200 prominent income-generating activities in manufacturing (both rural and urban) for over 30 years, including their use of electricity. It is not well understood how electricity introduction or changes in consumption differentially impact the financial situations of these income-generating sectors over time. This is due, in part, to many additional factors at the local, state, and national level that influence markets, energy supply, and politics to name a few. The aforementioned government data captures these interwoven influences and gives us the ability to see how the effects of electrification on economic activity changes over time. These historic trends might allow us to predict how these sectors will change in the future. This information is important when identifying when certain sectors may grow or disappear with the introduction and intensification of electricity usage and where or when more electricity is needed to support growth.
Using decades of data, the research assistant will help to understand the link between electricity usage and economic productivity for different income-generating activities across India. The research assistant will build on previous work at the national level and then work toward understanding trends at the state and district levels where the most important decisions are made on electricity infrastructure development. Based on historic data trends, the research assistant will use machine learning techniques to predict these trends and project future trends. Government agencies like the Central Electricity Authority of India (in charge of grid planning) would find this information particularly useful along with civil society organizations that promote sustainable livelihood growth of India’s underserved populations.
Research mentor: Michael Machala (Postdoctoral Scholar, Precourt Institute for Energy)
- The research assistant will be the primary researcher in this project with ongoing professorial and postdoctoral support; this is a significant responsibility to which you should commit.
- The research assistant work will include but may not be limited to: data cleaning, organizing, visualization, and analysis; exploring historic causes for certain data trend anomalies; report writing.
- Stanford undergraduate students in good academic standing are eligible to apply
- All majors are welcome
- Self-starter attitude, team player, eager to learn
- Respectful of timeliness, deadlines, and open communication
- Required experience: Big Data analysis using R, Python or another appropriate language; machine learning/AI experience; statistics experience; economics (basic)
- Preferred experience: Stata experience will be useful but can be learned; experience with demographic datasets
Time Commitment:
10-15 hours per week during the academic year
To Apply:
Along with the application, applicants are asked to submit a cover letter, resume or CV, and a Stanford transcript (if an incoming freshman, applicants need not submit a transcript for fall quarter applications).
