FAQ ●  Resources ● Giving
Select Page

Research Opportunities – Fall 2022

PLEASE NOTE: All the Fall 2022 RA Positions are now CLOSED.

The following faculty members, PhD students, and Postdocs 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 cs3899@columbia.edu to let her know who you will be working with, and also 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 NOTE: After the Waitlists are closed, you will need to Request to Add the course in SSOL.


PLEASE NOTE: All the Fall 2022 RA Positions are now CLOSED.


The following positions have been filled and are now CLOSED. Please do NOT contact the Researcher about these positions.


Seyhan Erden (Professor) – POSITION CLOSED
Assessing the attitudes of students toward econometrics
We will prepare a Likert-type questionnaire to collect data from students for assessing attitudes towards Econometrics course. Then, using SATS scale (used in Statistics courses), we will come up with scores in cognitive competence, difficulty, interest and effort that can be used by lecturers of this course.
A good grade in Econometrics course. Knowledge of Stata or R. Interest in brain storming to prepare a Likert- type questionnaire and compiling data. The questionnaire will be administered on the last day of the classes, so interested students need to be available to do some of the work after December 12th (or sometime in January).

Gabriel Gonzalez Sutil
Heterogeneous Engel Curves and Electricity consumption in Rwanda: Do non-economic factors matter?
In 2009, the Government of Rwanda launched the Electricity Access Roll-Out program (EARP) to increase electrification rates. The Energy Access Roll-Out Project electrified more than 40% of Rwanda’s population in ten years. Yet, consumption is still low, which affects the sustainability of the system. How electricity consumption can be increased? Would economic growth alone solve the grid sustainability problem? The goal of this project is to estimate energy Engel curves for Rwanda using a semi-parametric model with a control function approach. Moreover, the project aims to explore the dynamics and mechanisms behind the Engel curve. The final goal is to inform policymakers about the patterns in electricity expenditure in Rwanda.
R programming and data cleaning skills. The RA will have 2 main responsibilities: (1) help me cleaning the household integrated survey (EICV); (2) work on visualizations and tables with simple preliminary analysis. If interested, the RA can provide help running the semi-parametric model (I do not expect the RA to know semiparametric techniques but if interested I can explain him what these are. I will use R to run these models, and I will run the models. If interested, I can allow him to help me in the process).

Matthew Davis
Global inequality in the climate century
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 the distribution of income.
I’m looking for someone to help process climate model output. In particular, the task is to take the output of a climate model which takes the form of a three-dimensional grid of temperature projections and calculate the global mean surface air temperature associated with each one. This will be done for hundreds of such projections corresponding to different combinations of climate models and emissions scenarios. Additional tasks may follow depending on progress. The main qualification is that the RA should be familiar with using R or Python to scrape and process datasets. Familiarity with using APIs to access data is a plus, but not required. This particular task is not econometrically involved, but completion of at least one econometrics course is helpful. Work will entail writing scripts to automate downloading large datasets from an online archive, quality-testing the data, performing the necessary calculations, and producing data visualizations. This will involve handling unusual spatial/geographic data and may entail using high-performance computing clusters, 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 thereof 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.


Dafne Murillo (PhD Student) – POSITION CLOSED
Land Ownership and Productivity: Evidence from a Peruvian Reform
This project studies a revolutionary land reform that Peruvian agriculture experienced in the 1970s. The reform (i) expropriated large landholdings or “haciendas” and gave them to predominantly indigenous peasants and (ii) promoted the (horizontal) integration of smallholder farms into communal ownership. Leveraging this natural experiment, we will investigate the effect of redistribution through reallocation of property rights on productivity.
We have secured access to a wide variety of historical data sources. Tasks will include digitizing sources to build a novel dataset based on this archival repository as well as reading and summarizing historical documents. Knowledge of Spanish is required. Knowledge of Python (ORC) is useful but not required.


Michael Best (Professor) – POSITIONS CLOSED
Two projects, as follows:

1) 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 an amount of letter grade credits determined by the department during Winter 2022, with possibility of extension into Spring 2022. Qualifications
  • 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

Dampening Natural Disasters’ Disruptive Effects on Firms and Labor Markets
The project consists of evaluating the impact of floods on labor markets in Brazil, as well as understanding how local governments can implement mitigation strategies to reduce the potential negative effects of such disruptions. One of the data sources being used are the Brazilian daily gazettes, which contain a huge amount of relevant information but are all in PDF format.
The student would provide assistance in extracting information from PDFs and organizing the data, where they would be working with the other research assistants in this project. The student needs to be fluent (ideally native) in Portuguese. Experience working with Python and R would be a big plus.


Seyhan Erden (Professor) – POSITION CLOSED
Learning Econometrics
I have data about students in Intro to Econometrics course for past 30 semesters. We will clean the data and research on what makes a “successful” student in the first undergrad econometrics class. The purpose of the research is to improve learning and teaching in this course.
I expect my RA to clean the data and run regressions. Advance Stata knowledge is required.

Qingmin Liu (Professor) – POSITION CLOSED
Empirical research supervised for Prof. W. Bentley MacLeod and Prof. Qingmin Liu
Help the professors analyze historical graduate school admission data.
College junior; familiar with R. The candidate will be interviewed by Prof. W. Bentley MacLeod and Prof. Qingmin Liu.

Florian Grosset (PhD Student) – POSITION CLOSED
Can Land Policy Change the Climate? Evidence from a Large Tree-Planting Program
Most studies of the economic impact of climate change assume climate to be an exogenous variable. However, human actions can alter local and regional climate, particularly via land use. We assess the local and regional climate impacts of the Great Plains Shelterbelt, a large-scale forestation effort in the 1930s in response to Dust Bowl soil erosion, a program that planted 220 million trees across six Midwestern states in the US. We show that growing season precipitation increased and temperature decreased in locations forested under the program, with impacts extending into adjacent unforested lands. Such climate effects persisted for several decades. Further, agricultural yields increased in locations that received more favorable growing conditions. This paper highlights the endogeneity risk in using spatial variation in climate trends for climate change damage estimates, as well as the potential for tree planting for both climate change mitigation and adaptation.
The primary task of the RA will be to conduct background research on existing large-scale tree-planting projects. They will thereby assist in comparing the program under study with current projects, and in discussing the research project’s implications for predicting the impacts of these massive land use changes. The secondary task of the RA will be to proofread the working paper, and to help prepare it for broader diffusion. This will entail conducting a detailed literature review on the effects of environmental and land-use policies on socio-economic outcomes, as well as on the drivers of structural transformation. No special skills are required for these tasks — except an appetite for environmental and historical economics. If the RA is skilled in the programming language R, the RA will also be able to review and verify the code used for data cleaning and analysis — thereby learning about impact evaluation applied econometrics while ensuring that no errors are affecting the results of the current analysis.

Carolyn Hayek
Tracking Onsite and Distributed Water Reuse Systems in the United States
Cities are learning to manage water resources more sustainably, which includes the use of onsite and decentralized water reuse systems (ODWRS). Learning from past experiences in other cities is difficult because documentation of existing ODWRS is scattered across many informational sources and varies widely in content based on the author. This project compiles information from multiple sources into a single profile for each identified system for inclusion in a publicly-available centralized database. This work is ideal for students interested in urban economics or infrastructure.
Manual and possibly automated data extraction of system-level details in an excel spreadsheet. Open to extension of tasks (with consultation) based on student interests.

Nicolas Longuet Marx
Party Lines or Voter Preferences? Explaining Political Cleavages.
This project studies the changing structure of political cleavages in the US: high education levels used to reliably predict right-wing affiliation in the 1970s but, starting in the early 2000s, this tendency was dramatically reversed. How can we explain these new political cleavages? 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? Disentangling these supply and demand effects is the objective of the present study, combining innovative tools from Natural Language Processing with very fine-grained election data and a well-tested demand model from the literature in Industrial Organization.
The RA will work on 2 distinct tasks, depending on their skills: first help to collect and unify election data at the precinct level for recent years (2018, 2020, 2022). Second, the RA would assist me with the scraping of additional campaign materials and the formatting for the NLP algorithm. Basic proficiency in Stata is required, and some experience in Python is a plus but not required.

Lena Song
Media, diversity, and inequality
I have several projects on media and inequality. For example, one project studies media diversity using evidence from US radio stations in the 1940s to 1960s. Research questions addressed include how racial discrimination affects media diversity, and how content on radio stations evolves over time. In other projects, I work with social media data and study social media and racial attitudes.
RA(s) will contribute to the construction of large, novel datasets. The ideal candidate should have basic programming skills and have some experience with STATA and/or python. Experience with OCR is a plus but not required.

Anna Papp
Plastic Pollution / Land Privatization and Cronyism
The RA will assist 4th year Sustainable Development PhD student with two projects (depending on interest/need). The projects are described below. Plastic Pollution: The absence of spatially disaggregated data on plastic scrap waste has previously prevented inquiry of the effects of air and water pollution from burned or discarded waste. This project uses machine learning on satellite imagery and crowd-sourced data to find and study the evolution of open-air plastic waste around the world. The project then exploits policy changes as natural experiments to identify the causal effects of plastic waste trade. Land Privatization and Cronyism: Land reforms are often rife with political corruption, yet the impact of cronyism on economic efficiency is ambiguous. This project investigates the effects of cronyism on agricultural productivity using data collected from a recent land privatization reform in Hungary. The project combines original data on political connectedness, rich information on the land auctions during the reform, and remote sensing data.
The RA will mainly assist with 1) data collection and verification and 2) literature and policy review. For both projects, there are careful data collections steps that the RA will help with. (For the plastic pollution project, this means verifying possible waste site with satellite imagery; for the land privatization project, this includes looking up information on agricultural plots to scale up analyses). Additionally, the RA will assist with literature review for both projects and a review of plastics-related policies for the first project. No special skills are required other than a general interest in environmental economics and careful attention to detail. Knowledge of, or eagerness to learn GIS and/or Google Earth Engine are a plus but not required. If the RA is interested in learning more about remote sensing satellite data and/or machine learning, they will have the opportunity to do so.

Tushar Kundu
Information and Bias in Technical Interviews
Interviews allow applicants the opportunity to demonstrate their skills so that employers do not have to rely on imperfect signals and self-reported information on resumes. This is particularly true for technical interviews, which are a common feature of hiring for high-wage technology jobs. However, these interviews raise scope for additional sources of bias, and in turn inequality of opportunity. In this project, we study data from technical interviews to understand sources of this disparate treatment in the hiring process.
The tasks would primarily involve data cleaning and creation, for example by recording information about audio files of technical interviews (emotions, number of interruptions, etc.) and classification of race and gender for existing profiles.


Sheena Iyengar (Professor) – POSITION CLOSED
RA opportunity for Professor Sheena Iyengar, Columbia Business School
Professor Sheena Iyengar is looking to recruit a couple of undergraduate RAs for the fall semester to join her team. RAs would report to her directly and would also work with her PhD students on projects at the intersection of behavioral economics and social psychology. This is a great opportunity for students looking to get involved in a research process and engage in both data work and literature review.
RAs will be primarily conducting literature reviews in the realm of the work and will also be involved in the various data collection + data analysis processes. Knowledge of R or Python would be a plus.


Michelle Jiang (PhD Student) – POSITION CLOSED
Labor and Networks
Traditional labor search models study how worker productivity, education, and experience affect hiring and wages, but don’t account for new evidence that individual’s friendships and networks can influence jobs. “Labor and Networks” combines user profile data from LinkedIn with mass layoffs data from the Worker Adjustment and Retraining Notification Act to answer the following question: Do larger or higher-quality networks cushion against negative employment shocks? The project is currently focused on the biotechnology sector, which has frequent mass layoffs due to clinical trial failure on the margin, but eventually plans to expand to other sectors.
I am seeking 1-3 RA’s with Python experience – particularly in numpy and pandas, and Stata experience. RA’s will have three assignments: 1) Read literature (weeks 1- 2 of the semester) 2) Work directly with the data: specifically, take basic Python code that creates network matrices and making the code (a) more efficient, and (b) expandable to larger datasets (weeks 3 – 11 of the semester). 3) Experiment with different methods of measuring networks (weeks 12-14 of the semester) A big plus is interest in the subject – I prefer a collegial environment, so you should feel comfortable bringing new ideas and thoughts to the table.

Niharika Singh
The Impacts of Collective Action on Women’s Livelihoods
Securing access to welfare entitlements remains a difficult problem for disadvantaged or minority populations around the world. In India, the flagship workfare and social protection program– Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS)– continues to face implementation challenges, limiting its effectiveness as an anti-poverty program. Despite being a self-targeted scheme on paper, poor households often find themselves excluded. We study how spurring collective action among low-caste women can improve their access to the MGNREGS and change their economic and social lives. To do this, we partner with an organization in Bihar that mobilizes low-caste women into ‘worker groups’ that collectively take action to access MGNREGS employment. We randomize the creation of the ‘worker groups’ across 127 groups of villages and measure impacts using publicly available MGNREGS administrative data and household surveys.
Based on interest and skills, the RA will be responsible for the following: – assisting with survey design and piloting – setting up data cleaning code and running it weekly for quality checks (using STATA) – compiling secondary research on wage-setting and wage bargaining in rural India – writing short reports and project briefs related to projects on other labor market topics Special skills if possible: proficiency in Hindi, familiarity and experience with data cleaning in STATA.

Waseem Noor
New course research
I would like help with research for a new course I am developing – The Global Economy (UN 2257) as well as updating research materials on some existing courses – Principles of Economics and International Trade. The research will involve examining current events that reflect economic activity. The student will have a chance to investigate different global events through an economic lens and will be more knowledgeable about real-world impact of economic policy by the end.
The student should have taken the core economic courses including – Principles, Micro and Macro. If they have taken International Trade it is a plus.


Jerry Shi (PhD Student) – POSITION CLOSED
Nominal Stock Price, Exchange Listing and Firm Financing Decisions
In this project we want to study how nominal stock prices affect firms’ equity offering decisions. It is not uncommon for small firms or financially distressed firms to use equity as a main source of financing due to their inability to use cheaper financing channels such as debt, and these firms are often in violation of the exchange listing rules regarding their nominal stock prices. Hence, exchange listing rules (such as those by NYSE and NASDAQ) provide a unique setting to study how stock prices could impact firms’ decisions of whether to issue equity or not, as long as firms value the exchange listing status and take actions to regain exchange compliance through reverse stock splits.
The RA would be responsible for data work (including data collection, cleaning and analysis), literature review, and other research-related tasks. Requirements: Interest in finance research. No specific skills required, but previous experience with data work and proficiency with R or Python is a plus.


Nadia Ali (PhD Student) – POSITION CLOSED
Evaluation of Matching Grant Program for Exporting Firms
This is an evaluation of a matching grant export-promotion program in Tunisia. 487 firms were randomized between a control group and a treatment group which receives a reimbursement equal to 50% of eligible expenditures. The goal is to evaluate the impact on firms’ export volume, number of products, and number of destinations.
The RA will assist in cleaning data from financial statements of firms (by checking firm entry against what is listed in financial statements and making any necessary adjustments), as well as generating summary statistics from survey data. The RA will gain familiarity with detailed firm-level data from a developing country. Knowledge of one of Stata/R/Python required; knowledge of French preferred but not required.


Utkarsh Kumar (PhD Student) – POSITION CLOSED
The Effect of Transport Disruption on Economic Activity
Developing countries frequently experience infrastructure failure – eg. transport delays, electricity outages. It is important to understand how costly these disruptions can be. This paper examines the issue in the context of transportation in India. The paper combines rigorous econometric analysis with structural modeling using tools from international trade.
The paper combines granular satellite data with different survey datasets in india. Ability to work with data – cleaning, analysis, producing output – is crucial. Must be comfortable with programming in either stata/R/python.


Serena Ng (Professor) – POSITION CLOSED
Changing trends in econometric analysis
Analysis of text/keywords
Knowledge of python programming is necessary. Knowledge of frequent item analysis is useful but not required.


Eugene Tan (PhD Student) – POSITIONS CLOSED
Three different projects, as follows:

1) Demand for Electricity Infrastructure
Getting to 100% household electrification is goal 28D in Rwanda’s National Strategy for Transformation (NST1) under the ‘Social Transformation Pillar’. Electricity *generation* assets as well as the high and medium voltage backbone *transmission* infrastructure of the electricity grid tend to be a public good that is centrally planned. Meanwhile, low voltage last-mile *distribution* connections from the grid to households typically funded to a lower extent than generation and transmission. Unlike generation and transmission, they are not centrally planned. They are demanded by households and supplied by the utility – a market. We analyze the market and its policies, implications for energy access.
*Both could eventually be paid in the Spring but no opportunity for co-authorship* 2 positions, one requiring: – Python and git skills. – Interest in learning to work with geopandas, making visualizations and maps – Academic interest in energy access or development or infrastructure Or speak Kinyarwanda – also opportunity to travel to Rwanda in Spring – this is mostly data collection, will be cold-calling people.

2) Envrironmental Standards in Production Networks
How are environmental standards in developed countries passed back through supply chains to their upstream suppliers? I study this using digitized shipping manifests, potentially one of the world’s biggest datasets on global trade.
Starting in mid-October, the RA will help me with making visualizations on production networks. e.g. Who are all of Nike’s upstream suppliers? Visualize subgraphs of firm-firm trade data starting from consumer products. Ideally, you have taken a course which has used basic graph theory (can you define a node, edge, subgraph?) and/or you know python/Javascript. Academic interests in the economics of supply chains or industrial ecology Big big plus if you know networkx or d3.

3) The impacts of gerrymandering and resettlement on deforestation
The Felda Land Development Authority (FELDA) resettlement scheme in Malaysia resettled about 112,000 rural Malay families into smallholder farms to grow cash crops – mostly palm oil – between 1958 and 1990. FELDA farmers have been labelled as a ‘vote bank’ for the ruling coalition, and some indicative evidence exists that they changed some political outcomes. My research question is whether the resettlement scheme changed environmental outcomes too.

  • Economic history/Political Econ/Environmental Econ paper.
  • Speaking Bahasa Malaysia is a plus, Bahasa Indonesia also can.
  • Early stage project.
  • Main task is to write memos, background information, literature review.


Kosha Modi (PhD Student) – POSITION CLOSED
Loan Covenants and Monetary Policy
The RA will help in the empirical section of my work related to Dealscan and Compustat database. Those interested in macroeconomics and finance are most suited. Comfort level with STATA is required.


Seung-hun Lee (PhD Student) – POSITION CLOSED
The impacts of political violence on the operations of local governments in Mexico
The project aims to identify the effects of the assassinations of municipality presidents in Mexico on various measures of local state capacity and economic activities. In particular, the project aims to look into various tax revenues, expenditure/supply of public goods, and the pool of potential candidates for future municipality presidents. The main goal is to assess how assassinations affect local public finance capabilities as well as quality of personnel in decision-making positions. Currently, I am looking for an RA who will assist in collecting various information on candidates for local elections in Mexico – from their names, age, affiliated parties, gender, and so on. Most of the searches will be done through browsing newspaper archives and websites for local election committees. Further directions will be delivered once the pool of RAs are finalized.

  • Since the projective RA is expected to browse through Mexican newspapers and election committee websites to obtain relevant data on candidates for municipal elections in Mexico (name/age/gender/party etc), fluency in Spanish is required.
  • In terms of technical skills, familiarity with web-scraping using python or R is preferred, but not required. (I will teach the basics and run the code together)
  • Familiarity with statistical packages such as STATA or R would be preferred, but not required.

Akanksha Vardani
Development Effects of Property Ownership Rights in Rural India
This project aims to understand the impact of property rights on development outcomes such as women’s bargaining power and property taxation. The project is divided into two parts. In the first part of the project I run an RCT and randomize property rights for wives in rural villages in Pune district of India and study the effects on women empowerment outcomes. In the second part of the project, I use the staggered implementation of a government land titling scheme in India to study the impacts on property rights on local taxation.
The tasks for the RA will involve collecting data from online sources, data cleaning, helping me in creating questionnaires for the surveys and data management. The individual should be conformable with MS Excel. Exposure to softwares such as STATA and R are welcome, but not necessary.


Marguerite Obolensky (PhD Student) – POSITION CLOSED
News Media Consolidation and Ideological Positioning
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 threefold depending on the RA’s interests and skills: (1) Write Memos on Federal Trade Commission regulations of the news media market; (2) Help with the collection of additional text data (e.g., from Associated Press); (3) Assist the research team with collecting newspaper characteristics (e.g., from Editors and Publishers).

Richard Clarida
Course Development
Assist in preparing PowerPoint outlines, charts for course development.
Excel, PowerPoint, downloading and charting data from FRED. Bloomberg a plus

Krzysztof Zaremba
Predicting Medical Malpractice: Machine Learning Approach
This project aims to use machine learning to predict medical malpractice among physicians in New York state. It explores the importance of referral networks, workplace changes and other characteristics to determine which physicians are likely to be disciplined by the medical board. To goal is to create and evaluate predictive model and publish it in a form of an online interactive dashboard.
Only skill needed is some ability to code in R or in Python. Machine learning knowledge is welcome, but not necessary. Your tasks would rely on finding and cleaning the data and helping in writing and evaluating machine learning models.

Shaoyu Liu
Bootstrapping Science? The Impact of a “Return Human Capital” Programme on Chinese Research Productivity
The project aims to understand a recent large-scale scientist recruitment program led by Chinese government on the productivity of recruited scholars and their local peers in host universities. It will help us to understand the impact of government role in boosting science and scientific competition across countries.
We are looking for student with interest in relevant topics with attention to details and ability to clean, manipulate and analyze large datasets. Programming experience in Python or R is strongly preferred.

Mark Dean
(Professor)  – POSITION CLOSED
Behavioral Economics RA
I need help with a variety of tasks related to my teaching and research in behavioral economics. These will include generating bibliographies for my class, and updating the website for the Cognition and Decision lab. The right candidate will also have the opportunity to get involved in other research projects.
Programming experience a plus, but to start with will only need to be computer literate enough to use google scholar and do simple website editing.

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.

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.
Translate »