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PLEASE NOTE:  ALL Fall  2023 RA Positions are now CLOSED.

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.

IMPORTANT NOTE: Students can only register for one Research project for credit. A 2nd project can be worked on for the experience only, and without credit.

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 cs3899@columbia.edu to let her know who you will be working with, and cc the researcher and Prof. Susan Elmes (se5@columbia.edu) 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 NOTEAfter the Waitlists close, you will need to Request to Add the course in SSOL.


Again, ALL Fall  2023 RA Positions are now CLOSED.


The following RA Positions are filled/CLOSED. Please do not contact the researchers about these positions


Luigi Caloi (PhD Student) – POSITION CLOSED
(with Prof. Michael Best)
Greener on the Other Side: Inequity and Tax Compliance
Do perceptions of unfairness and inequality in property tax liabilities contribute to delinquency? Combining administrative data on tax liabilities, payments and property transfers; reforms to the tax and liabilities in the different sectors, and an experiment informing households of the tax liabilities of other sectors, we study whether perceived unfairness affects tax payments.
We need to scrape the price and address of each property from this website: https://www.zapimoveis.com.br/aluguel/imoveis/am+manaus/. Any programming language that the RA is familiar with will be fine for this position, as long as it is feasible to perform this task. We can also guide and provide example codes for web scrapping with R.


Susan Elmes (Professor, DUS) – POSITION CLOSED

Radi (GS’23) and Kyla (CC’24) are working on a website known as EconVision (https://econ.vision/) that provides students with interactive visualizations of economic models to enhance their learning. Through the user-friendly interface, students can effortlessly explore graphs of the models that they encounter in their coursework.
Our day-to-day work involves coding new calculators, writing instructions and explanations, designing the website, and improving the calculators’ functionality. Professor Susan Elmes is our faculty advisor and we receive credit as research assistants for our work.
We are looking for another person to join us on the project. The person should:

  • Graduate in 2025 or later
  • Have taken Principles of Economics
  • Plan to pursue a major/ minor in Economics
  • Possess strong economic intuition
  • Be interested in technology and education, and the mission of EconVision
  • Have strong teamwork skills and dedication
  • Coding experience is desirable but not required

The commitment level is at least ~4 hours a week and a weekly 1-hour meeting. You will receive 1-2 academic credits for your contribution to the project.


Michael Best (Professor) – POSITION CLOSED
Fighting Corruption in Peru
Governments around the world rely on citizens to assist in the fight against corruption. Governments have limited capacity to monitor all aspects of government activity, and so citizens volunteering their information and their time can potentially drastically increase the arsenal at the government’s disposal. However, citizens have their own interests and may not possess the same training and capabilities as government workers. The Contraloría General de la Republica (CGR), the Peruvian government’s auditing agency, is the main organism undertaking large-scale actions to combat corruption. The CGR has been undergoing a massive reform focusing on strengthening its presence outside major cities and incorporating modern technologies in its auditing processes. In this effort, the CGR partnered with Columbia University and the Inter-American Development Bank (IDB) to undertake and empirically evaluate the impact of two large-scale policy innovations. Our first project asks how best to delegate the monitoring of public works projects to citizens, accounting for heterogeneity in their motivations and their ability to perform complex audit-related tasks. Ultimately, though, only governments can investigate and sanction public officials, but they have limited resources at their disposal with which to do this. Therefore, governments need to process citizens’ reports of malfeasance and rank them by priority. However, when capacity to prioritize citizens’ reports is limited, this can lead government anti-corruption efforts to be misdirected. Our second project asks how technology can be leveraged to process large volumes of incoming citizen reports and triage them.

The Research Assistant will work closely with the Senior Research Assistants to:

  • Assist in data cleaning and data analysis Assist in survey design and programming
  • Assist in the creation of reports to government partners
  • Assist in the preparation of literature reviews and qualitative research
  • Assist in project related logistics tasks
  • Perform other tasks assigned by the supervisors. The ideal candidate is an undergraduate student majoring in Economics or related fields with interest in early exposure to economics research and available to work for 5-7 hours a week for a letter grade and credit, with the possibility of extension into Spring 2024.


  • Strong oral and written Spanish communications skills
  • Self-starter, resourceful and detail-oriented with excellent organizational skills
  • Demonstrated ability to work independently
  • Demonstrated ability to work successfully handling various tasks
  • Eager to learn, and gain experience
  • Familiarity with randomized controlled trials is a plus
  • Prior knowledge of quantitative data analysis packages is a plus (ideally Stata)
  • Knowledge of the Peruvian context is preferred


Florian Grosset (PhD Student) – POSITION CLOSED
Commuting as a barrier to women’s employment in lower-income countries
Job seekers widely rely on their networks for employment. Yet, little is known about how individuals’ employment prospects affect the labor supply of their network members. We conduct two field experiments testing for complementarities in employment in Cote d’Ivoire. Job seekers are 52% more likely to accept a factory job offer, and 83% more likely to have it retained four months later, if their network members are also offered a job–but only if they would be working the same shift. We replicate these results with sales jobs, varying both whether the network members would be working in the same or different worksite and commuting time. Safer and more pleasant commuting is a key driver of the estimated complementarities, especially for female job seekers. Hiring network members together does not come at a productivity cost, but increases volatility: while on the job, co-commuters coordinate both their absences and quits. Our results have implications for firms and policymakers aiming to increase employment and reduce poverty.
The RA will be responsible for creating visualizations of key data elements underlying the project — which will be included in the paper and associated presentations. Among others, the RA will visualize where job seekers live in Abidjan (the economic capital of Cote d’Ivoire), where their network members live, where jobs are located, and their commuting patterns. The RA will therefore need to have a working knowledge of R, ideally but not necessarily with experience in spatial data visualization.


Nicolas Longuet Marx (PhD Student) – POSITION CLOSED
Party Lines or Voter Preferences? Explaining Political Realignment
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 the 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 and GIS would be an advantage.


Abhishek Deshwal (PhD Student) – POSITION CLOSED
The Dynamic Effects of Electricity Supply on Indian Industry
The project aims to uncover the dynamic effects of electricity shortages on Indian manufacturing. Since 2010, firms have moved away from self-generation of electricity while reliance on the electricity grid has increased dramatically. This is likely to have an impact on how issues of grid reliability, such as power blackouts, intermittency, etc affect production. The effect would be moderated by firms’ insurance mechanisms to outages, such as availability of self-generation, but such mechanisms require capital and are costly. This project, hence 1) aims to undercover how the industry’s sensitivity of electricity supply has changed over the years, and 2) models self-generation adoption to understand the steady state effects on firm size, growth and capital.
Major work would be towards building a dataset for the Indian electricity sector from 2006 – Present. The data exists publicly as pdf/xls files on the government websites. This needs to be downloaded, or to be more efficient, scraped. Then, the RA would work on cleaning, processing and aggregating the datasets as consistent panels. Knowledge of Python or similar programming languages would be useful. Experience with web scraping, while useful, is not necessary as it can be learnt on the job, through resources such as ChatGPT.


Tarikua Erda (PhD Student) – POSITION CLOSED
The On-Campus Recruiting Labor Market
This is a survey-based study conducted by two PhD students, Tarikua Erda and Laura Caron. The project uses the job search/recruiting process at college campuses to understand: (1) what employers value in candidates (and why) as well as (2) what job seeking students think employers value, which types of students have a more/less accurate understanding of what employers value, and how their (in)accurate perception may factor into their job offer and salary outcomes We are surveying both employers and job-seeking students participating in the campus job search/recruiting process and Columbia and other universities in the 2023-2024 academic year. The project would be ideal for students interested in learning more about labor economics, experimental research methods, and more broadly, about how higher education factors into inequality and social mobility in American society.
The RA would help with preparing inputs and materials for the surveys of this project. This includes: searching for the contact information of employers, cleaning and classifying information collected from job seeking students’ resumes, analyzing data (using Stata and R) to understand employer preferences. Strong communication skills, time-management, and reliability are a must as some tasks will be time-sensitive. Knowledge of Stata and R would be a plus.


Victoria Mooers (PhD Student) – POSITION CLOSED
1) Social Networks 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, networks, and/or social media. 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. Experience with Stata and/or Python is required.

2) Return to Sender: The Post Post-Partition in Ireland
This project will explore the impact of losing local post offices on Irish communities’ short and long-term social capital development. In early 20th-century Ireland, post offices played a vital role in the identity of Irish communities. Postmasters and postmistresses served as founts of local knowledge, registered pensions, and transferred information between communities. The Post Office’s significance was acknowledged: “…the Department [Post Office] in all its operations is more closely connected with the interests, accommodations, and personal feelings of every class of his Majesty’s subjects, than any other branch of the state” (Papers relating to the Post Office 1834, p. 9, H.C. 1834 [48] xlix, 497). In 1921, an international border partitioned Ireland into two self-governing polities. This border bifurcated existing municipal boundaries, including those of post offices. Several border communities suddenly found themselves without their longstanding postal employees. Informally, some report feeling the repercussions of this loss today as a weakened sense of community identity.
This project is ideal for students interested in historical economics. The RA’s primary task will be to collect geographical data from digitized archival documents with care and precision. Geographic literacy, attention to detail, knowledge of Excel, and the ability to work with large datasets are required. Experience with GIS is an advantage.


Hannah Farkas (PhD Student) – POSITION CLOSED
FEMA disaster data digitization
The RA would be helping me create a dataset from online records from FEMA that have not yet been digitized. This would contribute to a project studying the impacts of hurricane disaster declaration on the labor market.
No technical skills needed! Task would be to read through records and enter information into a spreadsheet.


Jerry Shi (PhD Student)  – POSITION CLOSED
Impact of Graduate Education on Entrepreneurship
This research investigates the influence of graduate level education on entrepreneurship, assessing factors like the propensity to initiate businesses, the quality and sustainability of these ventures, and the benefits of graduate school networks. Historical beliefs have positioned formal education and entrepreneurial tendencies as separate, but graduate studies may offer unique advantages to budding entrepreneurs. Through quantitative analyses, the study aims to provide insights that could guide educational institutions, policy makers, aspiring entrepreneurs, and investors.
Attention to detail; ability to clean, source and manage big datasets; ability to document findings in clean and concise manners. Coding – Familiarity with R or Stata or Python is preferred


Surabhi Ghai (PhD Student) – POSITION CLOSED
Social Networks and Internal Migration
This project is on how social networks can explain internal migration in the US. In the event of economic decline, population in an area is slow to move. I am trying to study whether attachment to the local community and social network can explain this phenomenon, as well as whether social networks can explain where some people might move. While this is the main project for the RA role, I also have another project that I may occasionally ask for help with. This project will be on how firms in developing countries respond (by adopting products, technologies, etc) when a patent in the US expires.
RAs will be involved in gathering data, doing literature review, as well as helping with analysis if they are familiar with computer programming. Familiarity with Stata, R, or Python is preferred but not required.


Daniel Bressler (PhD Student)  – POSITION CLOSED
The Mortality and Social Cost of Greenhouse Gases
This study will use the latest climate, socioeconomic, and epidemiological models to quantify the project number of premature deaths caused by climate change. Questions that we will address include: How many temperature-related excess deaths are projected to be caused by climate change? How many lives can you save from reducing carbon dioxide, methane, and nitrous oxide emissions? Both on the margin (e.g., replacing a coal power plant – given by Mortality Cost of GHGs) and by Non-marginal large-scale policies (e.g., the Inflation Reduction Act)? We will address other questions including: how do rising incomes affect climate change deaths? How does the Social Cost of GHGs change with choices around valuing lives and livelihoods in different parts of the world? And how does “optimal” climate policy and carbon pricing change with choices around valuing lives and livelihoods in different parts of the world? This project will use the new RFF-Berkeley GIVE integrated assessment model as the primary tool to address these questions, along with a variety of mortality damage functions. In addition to addressing the questions above, we will use this new model to re-estimate the mortality cost of carbon, which I had previously estimated in my paper that came out two years ago https://www.nature.com/articles/s41467-021-24487-w (see my website rdanielbressler.com for other related links including writeups in the media on the paper). But that paper worked with an older generation integrated assessment model (DICE) that had an outdated climate model and did not account for uncertainty in climate and socioeconomic projections. This project will improve upon the mortality cost of carbon estimate in the prior study in all of these ways and will be able to address the variety of new questions mentioned above.

The RFF-Berkeley GIVE model is coded in Julia (which is similar to python). We will be doing development of this model through Github. The primary task is support in doing the coding to answer the questions I listed above. An interest in this area is very important as is critical thinking (as much of the work involves understanding how various pieces of the model interact). Coding experience with Julia or python is strongly preferred.


Matthew Davis (PhD Student) and Tushar Kundu (PhD Student) – POSITION CLOSED
The RA will be supervised by two PhD candidates working on independent but complementary projects.
(1) Davis: Weather shocks, gendered violence, and cultural transmission
My project aims to merge open questions about the relationship between economic development and gendered inequality with an emerging empirical literature on cultural transmission. This is part of a collaboration with a political scientist in which we try to measure and explain the differential persistence of gendered behavior, violence, and institutions. The particular study the RA’s work would be contributing to focuses on intergenerational transmission.
(2) Kundu: Marriage Transfers and Signaling in Female Education
We study the role of labor market and marriage market considerations in motivating investment in female education. We consider increases to access to education, and allow shifts in educational attainment to vary based on marriage payment norms. We find that shifts are attenuated among populations that practice marriage payments. In the coming semester, we hope to clean additional data to incorporate and build on these findings.
The RA will primarily be tasked with exploring and processing a large repository of survey data from India to evaluate their relevance to our projects. We would ideally meet at least once every two weeks with semi-regular informal communication between meetings, e.g. using Slack for clarification or to troubleshoot coding issues you may (i.e., will) run into. Prior experience with a programming language is of course preferred—especially R—but more important is that the RA be very organized. Depending on progress and interest, the RA may also be assigned tasks for other projects broadly in the spheres of applied micro or enviro. Potential applicants are encouraged to reach out with any questions. If applying, please include your availability on Mondays this semester (not set in stone but most convenient for us).


Jesse McDevitt-Irwin (PhD Student) – POSITION CLOSED
Sex Ratios in Sub-Saharan PhD Student Africa
Childhood sex ratios are a useful indicator of maternal-infant health, especially infant mortality and fetal loss. These childhood sex ratios can be calculated from population by age and sex tables, which are often available from published census volumes. For sub-Saharan Africa, published census volumes are often available online as PDFs; the goal of this project is to find these volumes and enter them as machine-readable data.
The RA will help find published census volumes online and in libraries, and then transcribe selected data from the PDF to a spreadsheet. OCR and natural language processing skills are NOT required, as this will be hand transcription. French and Portuguese language skills would be useful, though not required.


David Weinstein (Professor) – POSITION CLOSED
The Meiji Miracle in Comparative Perspective: Productivity Growth and Learning From the West
The industrial revolution was a watershed moment in human history, marking the beginning of long-run sustained economic growth. Whereas the West experienced and benefited from industrial development, the rest of world fell behind. In the non-Western world, Japan was the first and one of the few countries to join the league of developed nations. A strict autarky in 1800 with a small pre-industrial economy, by 1910 Japan had become one of the world’s strongest industrial powers. What did Japan do achieve such formidable economic development when its neighboring countries floundered?
We believe that part of Japan’s success is due to a massive translation effort that made Western technological knowledge available in Japanese. Building a steam engine is much easier if the word “steam” and the instructions manual exist in your language. Accordingly, we found that Japan was the only country in the world where the sectors that experienced the highest productivity growth where precisely those with the most to learn from novel Western scientific research. We are almost certain that Japan was the only non-Western country to translate modern scientific knowledge to its own language during the industrial revolution. To verify this claim, we need to know how many technical books were available in Arabic, Bengali, Chinese, Hindi, and Korean between 1800 and 1910.

We are looking for a Research Assistant to scrape the catalog of a major Chinese library. Importantly, since we work as a team, we seek an assistant who can deliver a clear and well-document piece of code, that the other collaborators can easily replicate.


  • Native or near-native knowledge of Mandarin Chinese
  • Strong coding skills in Python and experience writing web scrapers
  • Some experience writing web scrappers
  • Some formal training in Computer Science is strongly preferred (an introductory or data structures class will suffice)


Belinda Archibong (Professor) – POSITION 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 using evidence from Nigeria.
Literature review, Data cleaning and analysis. Skills with Excel required, Skill with R/Stata preferred

2) Choking on Black Gold?: The Effects of Air Pollution from Gas Flaring on Human Capital Outcomes
We study the effects of air pollution from gas flaring on human capital outcomes.
Data cleaning and data analysis and literature review. Skills with Excel, R/Stata needed.

3) When Women March: The Effects of Women-Led Protests on Gender Gaps in Political Participation
We study the effects of protests on gender gaps in political participation using evidence from Nigeria.
Data entry. Data cleaning and analysis. Literature review. Skills with Excel needed. Skills with R/Stata preferred but not necessary. Careful historical analysis needed.


Seyhan Erden (Professor) – POSITION CLOSED
Learning Econometrics
Learning econometrics through visual interactive graphical simulations (this is an innovative course design grant that has started already, we are in need of students who can assess simulations and give us qualitative and quantitative feedback about each simulation throughout the semester)
Must know Stata very well.


Anna Papp (PhD Student) – POSITION CLOSED
Climate Change Adaptation and Gig Work
I study the use of gig economy platforms (e.g., UberEats) as a form of climate and environmental adaptation and consequent effects on the labor market in Mexico. First, I investigate whether consumers order more food delivery in response to risks such as extreme temperatures, rainfall, and pollution. Then, I study the consequences of these adaptations on the labor supply of gig economy workers.
I am looking for an RA who is proficient in written Spanish. The main task of the RA will be helping me with tasks related to a Mexican labor force survey, e.g. identifying or translating questions or interest. The RA may help with other tasks related to the project (literature review, data cleaning), depending on interest and skills. Knowledge of R a plus, but not required.
2) The Effectiveness of Plastic Bag Regulations
This project examines on a large scale the effectiveness of plastic bag policies (e.g., bans and taxes) in reducing plastic debris in the environment. To do this, we collect comprehensive data on town, county, and state level US plastic bag regulations and use crowdsourced clean-up data to measure plastic pollution.
The RA will help check data on US plastic bag policies and collect supplementary data (e.g., the text of policies). The RA may also help with literature reviews and data collection/analysis, depending on interest and skills. Knowledge of R a plus, but not required.


Ruixue Li (PhD Student) – POSITION CLOSED
Can climate protests backfire?
We would like to study if climate protests, especially those that cause social disruptions, backfire in the sense that they reduce public support for pro-climate policies. We will mainly be using the event study method and a variety of outcome variables, including social media, voting/consumption data, etc.
Depending on the programming skill of the RA, they will be responsible for data collection (collecting data for climate protests, voting, etc), data cleaning, and processing. Desirable skills: python and stata programming. Familiarity with social media data/ natural language processing methods is a huge plus.


Kosha Modi (PhD Student) – POSITION CLOSED
CPI announcements and Market-Perceived Sources of Inflation
We study the changes in asset prices around CPI announcements, such as Fed funds rate, nominal yields, S&P500 index etc. Using the direction and magnitude of these changes, we try to understand what the market believes is the persistence as well as the source of the inflation surprise. We do this through the lens of a model founded upon Lorenzoni 2009.
STATA, Matlab


Waseem Noor (Professor) – POSITION CLOSED
1) Global Economy Course Update
The Global Economy course will be taught in Spring 2024. This project will create a case study for the course, update the weekly readings for the course, and suggest ideas for the exam and midterm. The student could also be a Teaching Assistant for the spring semester.
Good research skills, ability to work with Excel, PowerPoint and Word, and an interest in international economic issues a must. Preference for students who have taken International Trade (with Prof Noor if possible). Avid readers of the Economist and other periodicals and newspapers are encouraged to apply.

2) Principles of Econ Course Update
The Principles of Econ class is being taught in the Fall and Spring semester of this academic year. This project will help catalogue and critique questions from problem sets, midterms and finals from the past 5 years. The RA will also help with suggestions for future questions.
Strong organizational skills, ability to work with Excel, PowerPoint and Word, and a broad interest in economic issues is a must. Students should have completed the core courses and declared an Economics major. Preference for students who have taken Principles with Prof Noor.


Donald Davis (Professor) – POSITION CLOSED
A Spatial Economic History of New York City
The aim of this project is to understand the history of economic development of New York City, especially in spatial dimensions. As such, this will require thinking about how New York City fits into the global, national, and local economies in different historical epochs, as well as how over time this spills over into the evolution of economic space inside of the New York City and Metro areas. While a great deal of the early effort will focus on assembling and analyzing data on the basic economic structure of the city and how this has evolved, this will always be done with an eye to understanding the political and social contexts that frame and interact with the economic structure.
Essential tasks for the RA will include identifying for different time periods relevant data sources, assembling and analyzing the data. Proficiency in R, including mapping functions would be highly useful. Comfort with digitization of some historical sources likewise. A genuine interest in the topic at hand would be great, since some of this will require creativity in thinking about new data sources that may be developed to address issues that standard sources may not cover. I will work closely with the RA, but also value resourcefulness in solving problems. Strong organizational skills.


Suresh Naidu (Professor) – POSITION CLOSED
The Effects of Labor Organizing on Worker Outcomes
Project evaluating a midwestern labor market reform, quantitatively and qualitatively. Project entails collecting public data on health care facilities. Project involves a team of economists and sociologists.
Need a student to look through health care facility webpages and record details of vacancies, benefits, and other information. No particular skills required so perfect for sophomore students looking to get a bit of exposure to research. Would like commitment of at least 50-80 hours of work over the semester.


Maya Norman (PhD Student) – POSITION CLOSED
Commodity Prices and Recycling Supply
This project will explore how variation in commodity prices such as aluminum and copper impacts the supply of metal to recycling facilities throughout New York State. The wage paid for selling used metals varies with the commodity prices. Thus, we will estimate how informal labor supply varies with the recycling wage.
Main task: convert pdfs documenting the amount and type of metals received at recycling facilities to an excel file.


Gabriel Gonzalez Sutil (PhD Student) – POSITION CLOSED
The effects of in-house experience and inertia on multi-unit firms’ compliance and technology choice
Achievement of environmental objectives, and minimization of the cost of such achievement, are dependent on the diffusion of abatement technologies. Since these technologies only serve to reduce emissions, incentives to adopt them must come from environmental regulation. This project uses data on NOx abatement technology and studies power plant operators’ adoption decision in US electricity markets. In particular, the project studies how technological inertia affected the diffusion of these technologies and its implications for policy design.
The RA will help in the construction of the dataset and the econometric modeling. Several unique datasets are being used in the project. The RA will assist me in combining all the datasets and creating relevant variables to use in the empirical analysis. Finally, the RA will assist me with the econometric modeling. This paper uses a did-dif survival analysis. Most of the script are written in R. Some basic econometrics (IV and OLS) is required. Ideally, the RA will have some basic understanding of maximum likelihood estimation.


Clara Berestycki (PhD Student) – POSITION CLOSED
Firm’s reactions to Climate Policy Uncertainty
This is a project in environmental economics. We have built an index measuring climate policy uncertainty using press data. We are conducting empirical econometric analysis of the effect of climate policy uncertainty (through our index) on firm-level outcomes such as investment and market-level outcomes such as stock market returns. Leveraging precise data on firms’ CO2 emissions, we find that firms in Co2-intensive sectors react more negatively to periods of high uncertainty than firms in less Co2-intensive sectors.
The RA would perform explanatory data analysis of Co2 data and maybe collect press data for the index using Factiva. Other tasks could include data collection, exploration, and cleaning for other data sources. All in all, a data exploration and data cleaning tasks. Proficiency in STATA, R, or Python would be preferred.


Eshaan Patel (PhD Student) – POSITION CLOSED
Voter Responsiveness to Government Failure: Evidence from the 2021 Texas Winter Storm
Do voters lose faith in a government that fails to adequately serve the populace? In particular, this project looks at voter responsiveness to a widespread and severe disaster in Texas. I use data on county-level variation in power outage severity along with county-level election data. The project is in the early stages, which would be a great learning opportunity for an RA to work with the data to explore these effects.
The RA would have relative freedom to explore this new dataset that I’ve collected, run regressions, and find novel patterns in the data. Some knowledge of coding, especially in STATA, would be helpful, but it is fine to build those skills during the project for those who lack prior experience. Same goes for econometrics skills.


Matthias Buchta (PhD Student) – POSITION CLOSED
Machine Learning in Financial Markets
This project is in its early stages and may go in various directions. On the theory side, I am interested in why machine learning models (e.g. neural networks) have recently been shown to have higher out-of-sample predictive power for asset returns than much more parsimonious models, which is in strong contrast to the traditional view in financial econometrics, where parsimony is a key concept. On the empirical side, I am e.g. interested in using alternative data (textual/image/social media data) to predict the movement of asset prices, ideally in an intraday-frequency setting.
The specific tasks depend on the skillset of the RA but may involve data collection/cleaning/analysis as well as review of the pertinent literature. The RA should have a solid understanding of statistics/econometrics and should be proficient in Python. Prior knowledge of Machine Learning concepts (e.g. ridge/lasso regularization, neural networks, NLP) and financial markets would be ideal but is not required.


Douglas Almond (Professor) – POSITIONS CLOSED
1) Greenwashing Trends in Corporate Logos
We plan to assess how corporate logos have become more green or environmental appearing over time. We’ve identified a database of corporate logo images and plan to link these to individual firm stock prices. We may also use a machine learning algorithm to help assign perceived greenness. Research project is joint with Eric You (Michigan) and Xinming Du (National University Singapore)
The main task is to scrape corporate logo information from the largest 500 US firms from an online database we’ve identified. We want to store data all fields in a .csv and also capture the logo image itself in a .png file.

2) Evaluating an Airline Initiative to Reduce Plane Contrails
Contrails form when planes pass through humid cold air and contribute to global warming. They can be reduced by altering the altitudes at which planes fly depending on weather conditions. We plan to evaluate the impact of an airline initiative to reduce contrails on satellite and ground-based measures of clouds along flight routes, and include any observed temperature effects by altitude. Project is joint with Prof. Xinming Du at National University of Singapore.
We’d like to learn as much as possible about the airline’s program itself — which planes, which routes, when, etc were most likely to alter their flight altitudes so as to reduce contrails. This will include online searches for background program information, including an AI project by Google to predict humid levels by altitude that would likely form contrails. Assuming we detect impacts of the program, RA would also be asked to conduct literature review of the impacts of cloud cover on humans, e.g. mood and sentiment.


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Mon–Fri, 9:00 a.m.–5:00 p.m.

1022 International Affairs Building (IAB)

Mail Code 3308

420 West 118th Street

New York, NY 10027

Ph: (212) 854-3680
Fax: (212) 854-0749
Business Hours:
Mon–Fri, 9:00 a.m.–5:00 p.m.
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