Summer 2021 Research Assistant with Marianne Bertrand
This internship is part of the University’s Jeff Metcalf Internship Program. Please review the Metcalf Interns’ Responsibility Notice to learn more about program requirements for Metcalf interns.
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Faculty
Marianne Bertrand
Project Description
The research project would be focused on studying Female Labor Force Participation and Tertiary Education Enrollment in the Indian Context and is a collaborative effort led by Professor Marianne Bertrand.
One specific initiative is to understand how the increased presence of higher education institutions and schools impacts female education enrollment, and labor force and marriage market outcomes. This work requires usage and processing of multiple panel datasets, ranging from data on higher education institutions to Indian census and surveys administered to samples of the Indian population administered by the Center for Monitoring the Indian Economy.
Potential tasks would involve:
- Cleaning and processing such data in R and STATA. This involves writing efficient code, especially as the data can get rather large; it also requires attention to detail and investigation potential issues or inconsistencies across the data and potential fixes.
- Geocoding institutions to appropriate localities using software such as Google Maps API and/or ArcGIS.
- Formulating and setting up regressions and analyses to investigate the research question. An understanding of concepts such as instrumental variable regressions would be useful.
A related project that would run in parallel would be focused on studying specific factors that affect female labor force participation in the Indian context through the setup of a Randomized Controlled Trial (RDC). The project would aim to investigate the influence of social factors such as norms and stereotypes on female labor and social outcomes. Management of similar data on human surveys would be required alongside tasks specific to an RDC, such as designing survey questionnaires.
The work would be iterative in nature, with updates to code and procedures required as new information is produced. It requires strong collaboration and communication with PIs and Pre-Docs.
Start and end dates are flexible.
Required Skills
Experience with R and STATA is strongly preferred. Training in Econometrics and basic familiarity with geocoding software (GMaps API, ArcGIS) is preferred but not required.