PLEASE NOTE: All Spring 2023 RA Positions are now CLOSED.
Research Opportunities – Spring 2023
The following faculty members and PhD students are seeking research assistants this semester. All of these positions are for credit.
PLEASE NOTE: Research Credit (GU4996 and GU4995) is only available to Undergraduates (CC,GS,EN and BC) and MAO students in the Department of Economics.
Selected RAs will need to register for a Research Course. Students registered for research course GU4996 will receive either 1 or 2 college credits and be charged for those chosen credits (relevant only to students who pay by the credit). GS (General Studies) students have the option of participating in a research project at no cost by instead registering for GU4995 for 1 credit, for which they will not be billed. However, in the case of GU4995, the 1 credit may not be used to fulfill the minimum credit limit of a Columbia degree.
In both cases, students will receive a letter grade on their transcript for their work as an RA. However, in either case, research credit may not be used as a substitute for elective or seminar requirements in the major.
If interested in an RA position, please do the following:
1. Contact the researcher directly at the email address provided, and include a copy of your Columbia transcript (unofficial is ok) as well as your CV/resume.
If you are selected as an RA by the researcher, continue with the additional steps below:
2. Contact Cathy Scarillo at firstname.lastname@example.org to let her know who you will be working with, and also cc the researcher and Prof. Susan Elmes (email@example.com) on your email.
3. You will then be sent a link to a specific RA form to fill out.
4. You will also need to join the waitlist for the Research Course GU4996 in SSOL (or the optional GU4995 for GS students only). PLEASE NOTE: After the Waitlists are closed, you will need to Request to Add the course in SSOL.
Again, All Spring 2023 RA Positions are now CLOSED.
The following positions have been filled and are now CLOSED. Please do NOT contact these researchers about the positions.
Seyhan Erden (Professor) – POSITION CLOSED
I am working on three separate projects on teaching/learning econometrics. One with 12 years of data, another one with a new questionnaire submitted in Fall 2022 and will be submitted in Spring 2023 as well. The last one is a project for an interactive platform for intro to econometrics students, this project will take about 18 months and it is done with with CTL.
Extensive Stata knowledge is required (producing tables, graphs for vast amount of data analysis). Also, organizational skills as well as written language skills are important.
Morgan Williams Jr. (Professor, Barnard) – POSITION CLOSED
Race and Criminal Justice
I am looking for an RA to assist with empirical projects assessing racial disparities in several important criminal justice domains (e.g., gun violence, policing, and prisoner reentry). These projects involve working with various administrative datasets related to criminal justice. The RA would be responsible for various data management and logistical tasks related to these projects.
Data management, programming (preferably in R), and institutional background research.
Florian Grosset (PhD Student) – POSITION CLOSED
Network Spillovers in Labor Supply Decisions
This project investigates how individuals’ labor supply decisions, including job take-up, attendance, and productivity, are influenced by their network members (friends, family, neighbors, etc). It does so using primarily a field experiment, conducted in Cote d’Ivoire.
The RA will mainly be responsible for conducting literature reviews on topics relevant to the project, spanning the social sciences (economics, sociology, history). The RA could also support the data cleaning and analysis, if proficient in Stata. Knowledge of French is a plus, but not required.
Tushar Kundu (PhD Student) – POSITION CLOSED
Estimating quality of life for students with special needs
In this project, I survey parents and teachers of special needs students in India to construct a measure of students’ well-being. The well-being measure incorporates progress on many dimensions of life, and incorporates student-specific weights that captures how important each dimension is to their well-being. I then run a teacher information intervention, in which I provide the information about students well-being to randomly assigned teachers, and observe the effect on teacher behavior, and student outcomes.
Tasks will be varied; they include survey design and management (experience with Qualtrics is a plus, but not required), literature review, and optionally work on related statistical models (R and Stan).
Nicolas Longuet-Marx (PhD Student) – POSITION CLOSED
Party Lines or Voter Preferences? Explaining Political Cleavages
This project studies the shift of blue-collar voters away from the Democratic Party. Democrats are now consistently winning in educated, cosmopolitan cities but have lost their grip on the post-industrial areas that used to constitute the Blue Wall. How can we explain this political realignment? Did left-wing parties decide to move away from working class voters to focus on the educated elite by offering different types of policies? Or, on the contrary, is the working class seeking out policies that are different from those it looked for in the 1970s? This project disentangles supply and demand effects in the political realignment, using tools from Natural Language Processing with very fine-grained election data in a well-tested demand model.
The RA will help in the data collection and data processing of electoral results for most recent elections. Depending on their skills, the RA will also help in the scraping and processing of political candidate websites. Knowledge of Stata is required, knowledge of Python would be an advantage.
Marguerite Obolensky (PhD Student) – POSITION CLOSED
News Media Concentration and Content Diversity
The dramatic rise in political polarization of recent years has fostered a renewed interest in the influence the structure of the news industry has on political outcomes. In particular, concerns about concentration and its impact on the political debate have grown but systematic studies of the efficiency of antitrust rules to ensure news diversity are lacking. How should policymakers regulate the industry when they place inherent value on news diversity and large publishers shape the ideological landscape? Building on recent advances in Natural Language Processing, we group articles into interpretable topics and estimate the topic coverage and ideological positions of 200 major U.S. daily newspapers using millions of published articles. Second, we embed these ideal points in a model of demand for differentiated products with heterogeneous readers and supply of ideological news. Ultimately, our model enables us to study counterfactual scenarios and give recommendations on antitrust rules weighing both consumer welfare and ideological diversity.
The Research Assistant’s tasks will be twofold: (1) Assist the research team with collecting newspaper characteristics (e.g., from Editors and Publishers Databook ) (~3weeks). (2) Collect information on newspapers owners (for this task, basic coding skills are preferred).
Dian Jiao (PhD Student) – POSITION CLOSED
Firms in developing countries
This project studies various reforms in India, including tax reforms, land reforms and bank reforms on firm productivity.
Clean and analyze firm and policy data. Knowledge about STATA or R is required.
Tianhao Liu (PhD Student) – POSITION CLOSED
The Impact of the Dual-Credit Policy on the Chinese Electronic Vehicle Market
The project uses the retail panel data from the Chinese electronic vehicle market to estimate the demand and supply side. We aim to use structural methods (e.g. BLP1995) to uncover the impact of the dual-credit policy. From there, we plan to study its welfare implications, and counterfactual outcomes under different policies.
Collecting and cleaning data; running basic regressions and providing summary statistics. Language: familiar with Chinese (the data sources are in Chinese); programming: R/Python/Matlab/Stata, etc.
Waseem Noor (Professor) – POSITIONS CLOSED
Econ MA Student for Econometric Research
1) We are looking for an Econ Masters student to help conduct econometric research around the progression of undergraduates through the Economics program. Please reach out by Tuesday, February 7 if interested.
2) Principles of Economics research
We will be conducting research to improve the Principles of Econ class. The RA will revise and add articles and podcasts for the weekly readings, as well as analyze trends on whether students are more or less likely to major in Economics after taking Principles.
Having taken Principles of Economics at Columbia preferably with Prof Noor is required. The student should have strong writing, powerpoint and Excel skills and be willing to meet every week for an hour to discuss progress. Having taken Intro to Econometrics is recommended but not required.
Hannah Solheim (PhD Student) – POSITION CLOSED
The On-Campus Recruiting Labor Market
This project explores (1) how employers weigh different aspects of candidates’ resumes (e.g., GPA, extracurricular involvement) and (2) how college students’ (mis)understanding of these preferences may affect job and salary outcomes. This project is ideal for a student interested in the intersection of labor, behavioral/experimental economics, and inequality.
Kate Musen (PhD Student) – POSITION CLOSED
Effects of Foster Care Reform in California
I am working on a project studying several policy changes affecting foster care children in California, including extended foster care (AB12), the closure of group homes (AB403), and extended Medicaid eligibility for children aging out of foster care under the ACA. I will be using the natural experiments created by these policy changes and data from the California Child Welfare Indicators Project to estimate casual effects on health, labor, and educational outcomes. California has one of the largest populations of foster care children in the country, so understanding the effects of its policies informs national discussions pertaining to child welfare.
I am looking for an RA to help me compile the details of all relevant policy changes and to track down the dates of shelter closures in California both prior and after AB403. I may also ask for help on some of my other projects in the domain of child health if time permits. I am much more interested in finding an RA who cares about these issues than one with lots of technical skills, as I do not need help with data analysis (and my data are restricted use). Attention to detail, organization, and tenacious Googling are the most important skills for this project.
Roman Rivera (PhD Student) – POSITION CLOSED
Policing and the Criminal Justice System
Variety of projects relating to policing in the U.S. using large administrative data sets from police, courts, and jails. Project focusing on connecting court outcomes to individual police officers.
Seeking R skills
Edward Shore (PhD Student) – POSITION CLOSED
How effective is CSR?
We assess the impact of CSR measures by looking at the example of the Equator Principles implementation. This program was designed to reduce the environmental footprint of projects financed by major western banks. We geolocate the projects and test whether joining the equator principles led to meaningful shifts in the environmental performance of associated banks.
Willingness to work with data.
Yeon-Koo Che (Professor) – POSITION CLOSED
Exploration of Carbon Markets
I am conducting an exploratory study of cap and trade mechanisms adopted around the world, with the aim of understanding the mechanics and design of the mechanisms and identifying potential drawbacks and exploring ways to address them. Eventually, I plan to collect trading data to evaluate the performance of the mechanisms and conduct counterfactual analysis on the effect of possible changes in the mechanisms.
The first task is to compile the list of cap and trade markets operated in the world and understand the details of how these markets operate and explain them to me. The second is to compile the references of existing studies on these markets. The third is to explore the availability of data. The final task is to perform basic statistical analyses of the chosen market.
Belinda Archibong (Professor, Barnard) – POSITIONS CLOSED
1) Information Frictions and Gender Inequality in Online Labor Markets
We study the effects of information frictions on gender gaps in matching and hiring in online labor markets. Administrative data from the largest online job platform in Nigeria suggest significant gender differences in job applications, hiring and potential mismatch by gender. Women are less likely to apply to senior level jobs, despite being equally qualified for positions. Women are also less likely to be hired. We implement randomized experiments that provide information on these patterns, along with diversity encouragement information, separately, to applicants and hiring managers. The results demonstrate the importance of the two sides of the online market and suggest that information can reduce gender gaps in employment by correcting misinformation among misinformed applicants and hiring managers.
RA with knowledge of statistical analysis needed to work on analysis of descriptive data, and data entry. Knowledge of Excel is needed, and knowledge of Stata/R is a plus though not necessary.
2) Role Models?: Examining the Effects of Nigeria’s NYSC Program on Educational Outcomes
Despite the proliferation of national youth service programs in many countries globally, particularly in African nations, and their frequent lauding as a model of an effective local government driven initiative, there is almost no quantitative study on the welfare impacts of these programs. We study the effects of these programs on human capital outcomes using evidence from Nigeria’s national youth service corps (NYSC) program, where recent post-secondary graduates or youth service participants are frequently placed in primary and secondary schools to serve as teachers. We study the effects of these NYSC participants on educational outcomes of young children in host communities: Do pupils that benefit from the presence of a corps member in their school perform better academically? And how do these effects, if any, differ by gender?
RA needed for data cleaning, data entry, literature reviews and simple statistical analysis. Knowledge of Excel is needed. Knowledge of Stata/R is a plus though not necessary.
3) Choking on Black Gold?: The Effects of Air Pollution from Gas Flaring on Human Capital Outcomes
What is the impact of air pollution from gas flaring on educational outcomes of young children? And can online learning apps help mitigate any negative impacts of air pollution on students’ learning outcomes? Gas flaring is a major source of local air pollution in oil producing countries and also a significant contributor to anthropogenic climate change. This research seeks to bridge the literatures on air pollution, gas flaring and human capital outcomes by first examining the impacts of air pollution from gas flaring on educational outcomes in children, and then testing the effects of access to online learning apps using evidence from a randomized experiment in Nigeria. Understanding the impact of air pollution from flaring on educational outcomes of children is especially important given the significance of human capital accumulation for economic development. The research proposes to examine these issues using data from surveys, fieldwork and tests conducted in Nigeria.
RA needed for data cleaning, data entry and data analysis. Knowledge of Excel is needed and knowledge of Stata/R and GIS is a plus, though not strictly necessary.
Solomon Gofere (PhD Student) – POSITION CLOSED
Birth Spacing and Children’s Birth and Long-term Outcomes
This study examines the relationship between birth spacing and children’s outcomes, focusing on the mechanisms that underlie the relationship. In particular, I use linked mother-child data from the National Longitudinal Survey of Youth (NLSY) to study the effect of birth spacing on the birth, school, and labor market outcomes of children. The study focuses on two mechanisms: the maternal health and physiology channel and the material and parental time input channel.
The RA is expected to download some of the National Longitudinal Survey of Youth data from the Bureau of Labor Statistics (BLS), clean, and merge them to an existing file downloaded from the same site. In addition, the TA is expected to do some basic descriptive analysis and a brief literature review. Intermediate knowledge of STATA or R is expected.
Jack Willis (Professor) – POSITION CLOSED
Dynamic poverty targeting
Developing country governments want their anti-poverty programs to target the poor, but when choosing recipients it is hard to know who is poor and who is not. A standard approach is to predict consumption poverty based on easily observable and verifiable household characteristics, such as the number of rooms in the home, the nature of house walls and floors, and the type of utilities available to the household. For this prediction task, we compare the performance of machine learning models to basic linear regressions (the status quo), and importantly how they compare when we predict poverty farther into the future, given that targeting rules are often in place for several years. The RA will be working with a team consisting Jack Willis (AP at Columbia), Eric Teschke (PhD student at Paris School of Economics), Muhammad Bashir (Pre-doc at Columbia).
The RA will primarily look for and prepare data from living standards measurement surveys of different countries (available at World Bank data library) that contains the variables described above. They will have access to sample datasets that we already prepared and we will guide them about each dataset and every step in this process. They can use any language to clean those datasets such as R, STATA or Python. They will gain familiarity with household survey datasets and poverty targeting methodology.
Stephan Thies (PhD Student) – POSITION CLOSED
Effects of public transit subsidies on the labor market
Especially in rural areas, firms often enjoy local labor market power which enables them to offer wages below the market rate because employees face high costs for commuting to other potential employers. We are investigating the impacts of a large scale public transit subsidy scheme in Germany on local labor markets. Subsidies to commuting costs might break firms’ wage setting power and could have large-scale distributional consequences that we aim to quantify. For our analysis we need to collect data on travel times and travel costs between different counties in Germany.
Web scraping travel times between German counties using publicly available APIs. Collecting information on travel costs and ticket prices from various transit agencies. Visualizing spatial data using Python, R or QGIS Skills: Python or R, ideally: knowledge of German
Hannah Farkas (PhD Student) – POSITION CLOSED
Historical redlining and current-day green spaces: effects of discriminatory housing policy on vegetation coverage
This project examines how historic discriminatory housing policies known as redlining contributed to current-day inequalities in urban vegetation coverage in American cities. There is well-documented correlations between lowest-graded cities and the level of vegetation, but limited casual analysis. I use a regression discontinuity design to determine causal effects of redlining, and use satellite data derived vegetation indices to measure greenery across 200 US cities.
For this project, I need to digitize roughly 200 historic census maps from the National Archives. Images of these maps are available online, but I need to georeference them and convert them into shapefiles using QGIS. The process is fairly simple and I can teach any RA who is interested in working with spatial data how to do this. It requires about 30-45 minutes per map, so having an RA to help me complete this task would be a huge help!
Susannah Scanlan (PhD Student) – POSITION CLOSED
Measuring Attention in Asset Prices / Asset Price Forecasts
Using rational inattention theory, I have developed a model to measure attention to different factors (e.g. real growth, climate risk, inflation,…) in forecasts that I am looking to apply to asset prices and asset price forecasts – i.e. what is the measured attention to climate risk in asset price forecasts? Work on the project would include: compiling, organizing and summarizing asset price data, earnings and price forecast data from IBES (and here creating a measure of forecasted change in asset prices by analysts), compiling data on alternative risk measures (extreme weather events, geopolitical risk), and potentially (depending on ability of RA and completion of data compilation) helping write a predictive factor model.
Language skills: MATLAB, R or Python (ideally at least some MATLAB). Familiarity working with Excel. Previous coursework: advanced econometrics class or time series class (a must); intermediate macro or finance (ideally).
Tristan du Puy (PhD Student) – POSITION CLOSED
Competition, Productivity and Peer Effects: manufacturing and US Chambers of Commerce
The project aims at studying productivity peer effects among firms, which would transform the way we think about the relation between market competition and productivity in industrial organization. Here, peer effects would happen through membership with the US American Chambers of Commerce. The focus will be on collecting the membership data from the US Chamber of Commerce from websites: making sure the websites are up to date, if the RA has a good knowledge of R or python, to help scrape the websites, and finally to help clean the data and run some descriptive statistics of that data (distribution across industry type, evolution over time, …).
Matthew Davis (PhD Student) – POSITION CLOSED
Climate change and global inequality
I use empirical methods to estimate the historical relationship between climate exposure and economic aggregates. I then apply these estimates to climate models projecting future climate change under a variety of socioeconomic and emissions scenarios to investigate the implications of future warming for global inequality and poverty.
The main qualification is that the RA should be familiar with using R, Python, or Julia to scrape and process datasets. Familiarity with using APIs to access data is a plus, but not required. The particular tasks I have in mind are not econometrically intensive, but completion of at least one course in regression analysis with programming is helpful. Work will entail writing scripts to automate downloading large datasets from an online archive, quality-testing the data, doing basic statistical analysis of the data, and producing data visualizations. This will involve handling unusual spatial/geographic data (particularly the output of hundreds of gridded climate model simulations) and may entail using high-performance computing clusters. Additional tasks may follow depending on progress and how the project evolves. This might sound intimidating but I expect much of this will be new and learned on the job both independently and with my guidance. I may also assign some reading to provide the RA with some context for their work so an interest in climate change and the economics is a plus. Ideally, I will meet with the RA every week or two and I will regularly be available for communication in between meetings.
Victoria Mooers (PhD Student) – POSITION CLOSED
Social Connectedness and Political Accountability
This project explores how disparities in voters’ exposure to information through social networks impacts how well the government serves different communities (in the US). I examine how the level of alignment between social networks and congressional boundaries impacts (1) how familiar voters are with their congressional representatives, (2) representatives’ effort, and (3) federal funding.
This project is ideal for students interested in political economy and/or networks. The RA’s primary task will be to assist with collecting, assembling, and analyzing data on surveys of voters, representative effort, federal spending, and media markets. Stata and/or Python skills are ideal, but candidates motivated to learn these skills should still apply.
Palaash Bhargava (PhD student) – POSITION CLOSED
1) Percolation of natural disaster related credit shocks through family networks
How does your family protect your credit health in the face of natural disaster related financial shocks? Do rich vs poor parents differentially share risk with their younger generations? Does this differ by how close-knit families are or how available diaster insurance is? How does the asset growth of one sibling impacted by the credit shocks faced by another sibling? What are the inequality consequences of differential risk sharing amongst rich and poor families? This project aims to answer these questions in the context of California by matching population-wide credit data to natural disaster events over the last 2 decades.
RA will aid and assist in the construction and compilation of several datasets including but not limited to natural disasters, terrain and geographical features of locations, insurance aid and disaster relief. Fluency in programming languages (Stata and Python) and ArcGis are preferred but not required
2) Role of historical institutions and endowments in preference formation
How does an individual’s ancestral history determine their present preferences and social actions? This project answers this broad question in the realm of cultural history, urban economics, behavioral and development economics. There are several different strands of this project. A few parts are primarily focused on construction of large scale datasets that can be used for long run growth analysis and others are more focused on looking at the role of historical institutions, climate shocks, famous personalities on an individual’s religious, social and cultural identity.
The RA will assist in exploring and constructing relevant datasets for several questions that are under the umbrella of this project. They might be required to clean, prune and code the data to make it ready for analysis. A hold over statistical softwares such as Python / STATA is strongly preferred but not required. Prior experience with text analysis will be helpful as well.
Sunil Gulati (Professor) – POSITION CLOSED
Sports Economics Prep
Preparation of various slides for use in Sports Economisc seminar. This would mostly involve creating summary slides from various data sources. Another piece could be some very basic research in thg sports economics area.
Excel and PPT proficiency.