Jerry Shi (PhD Student) ys3094@columbia.edu
Corporate Taxation and startup activity
We do not have very good knowledge of how startup activities are influenced by corporate taxation policies. This project aims to use statistical methods, i.e. changes in state policy variation as exogenous shocks, to study how startup activity changes. The results of the project will have policy implications.
Required skills: Coding in R or Python, Econometrics class/statistical methods, ability to work with large datasets. Attention to details and interest in learning about research.

 

Tatiana Mocanu (Professor) tm3326@columbia.edu
Equity and Efficiency Consequences of Racial Quotas in Hiring
This project will provide direct evidence on the effect of racial quotas on three margins difficult to empirically observe and measure: employer response to the quota implementation, quality of hired candidates under the new regime, and whether more minority candidates apply to jobs. Using variation from the introduction of a racial quota policy, it will leverage novel demographic and performance information in each hiring process stage of all applicants – both subject to the quota and non-minority candidates – as well as evaluation methods, job offers, and career progression. The study of long-term effects of quotas in occupations across several skill and education levels should provide valuable insight to employment-related policies in a variety of contexts.
The RA will work with large datasets of labor markets, including employment records, job admission selection processes, and performance on the job. Tasks will include data cleaning, processing, analysis, and interpretation. Intermediate to advanced coding skills (e.g. R, Python or similar language) are preferred, but not strictly required.

 

Sahila Kudalkar (PhD Student) s.kudalkar@columbia.edu
The role of bureaucratic incentives in environmental protection
The project examines whether political influence affects bureaucrat incentives for environmental protection. This project will test the impact of officer effectiveness in providing environmental clearances to infrastructure projects and whether officer performance impacts future transfers and promotions.
The RA is required to manually search Indian government websites for posting information of around 80 officers from the Indian Forest Services, and match these to an existing database on mining projects. They also need to identify the GPS coordinates of ~160 officer posting locations, and merge data with GIS files with information on (a) Rural/Urban, (b) Population size, (c) Education and health variables in the 2011 India census. Familiarity with R (sf, dplyr) and Indian government websites will be helpful.

 

Shuhua Si (PhD Student) ss5580@columbia.edu
Choice Complexity: A Representation Learning Perspective
This work combines machine learning with economic modeling and visits the classic problem of decision making under risk, seeking to (1) improve predictions by integrating ML and behavioral models, and (2) generate new behavioral hypotheses based on learned representations.
Implement model and data analysis in Python. Skills: Deep learning knowledge, proficient use of Python and PyTorch, knowledge of self-attention models would be preferred.

 

Luigi Caloi (PhD Student) luigi.caloi@columbia.edu
Tradeoffs of Discretion in Hiring School Principals in Brazil
Summary of the project: the quality of public sector employees is a vital component of the efficiency of governments, yet identifying high quality candidates for a position is a challenging task. In this project, we are partnering up with an NGO (Vetor Brasil) and a firm (Elos Educacional) that collect soft skill information on candidates for school principals in Brazil to develop a machine learning algorithm that predicts the quality of each candidate. The goal is to implement the algorithm in the hiring process through a partnership with a municipal or state government in Brazil.
Duty: in the short run, the RA will be responsible for communicating with Brazilian municipal and state governments. We can introduce everything else from the project and open for more collaboration.

 

Tianling Luo (PhD Student) tl3078@columbia.edu
Study on learning in sequential actions
We study under sequential (collective) actions, how people learn from others’ information and strategically decide when to participate.
Check proofs and solve/find examples. Strong mathematical background. Programming skill is a plus.

 

Zihao Li (PhD Student) zl3366@columbia.edu
Multidimensional Mechanism Design
Study the frontier of multidimensional mechanism design.
Read papers, generalize them to me, make slides.

 

Michael Best (Professor) michael.best@columbia.edu
Linking real estate data to property tax data in Manaus (Brazil)
The research team currently has geo-referenced administrative data on property taxes in Manaus and is planning to link this to the universe of residential properties for sale on the popular real estate site Viva Real. Scraped data from Viva Real includes characteristics of the property, the sales price, and its location plotted on Google Maps. These coordinates do not perfectly match to the GIS shapefile file of lot lines provided by the local tax authority. The RA will be expected to use Viva Real, Google Maps, and the shapfile data to match the property to its correct lot identifier. The project will entail manual matching/checking of ~7500 properties to the administrative data, which will then be used to link to the universe of property tax data.
The research team is looking for RAs who are comfortable working with large administrative datasets and possibly web scraping protocols. As the linking/checking of entries cannot be automated, knowledge of python or stata is not required (although always welcome). Familiarity with GIS programs is a plus, but the RA will be shown the specific tasks needed for successful completion of the task.

 

Junho Choi (PhD Student) jc5341@columbia.edu

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 2022 and 2024 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.

 

Jose Scheinkman (Professor) js3317@columbia.edu
Carbon prices and reforestation in tropical forests
We study the potential of tropical forest restoration to contribute to ameliorate the climate crisis.
Python and, if possible, experience with git/githib. Familiarity with R could replace experience with Python.

Roberto Zuniga (PhD Student) rz2516@columbia.edu
Climate Risk Information and Agriculture Adaptation
This project aims to evaluate a policy that provides farmers information about crop-specific risks related to climate conditions. We seek to answer some of the following questions: What are farmers risk preferences and beliefs?, to what extent farmers integrate the provided information into decision making?, and what is the cost-benefit balance of this policy?. The project involves tabulating risk data, modeling farmer behavior, and running counterfactual scenarios.
The first task is to tabulate the climate risk data. The data is in pdf format, and hundreds of pdf pages need to be processed. The RA will code a data extraction pipeline using some form of OCR and a coding language like Python or R. The RA will also check the results and handle potential exceptions. The second task involves working with raster data (maps) and performing spatial operations. We will average certain variables at both sides of district borders and then run a regression discontinuity design. In terms of required skills, some coding experience with Python or R is necessary. Python is preferred. Since the source data is in Portuguese, some basic knowledge of this language or even Spanish would be helpful, but not necessary. Previous experience with OCR or spatial data is also helpful.

 

Douglas Almond (Professor) Contact: vl2395@columbia.edu
Empirical Analysis of Corporate Logos
Our project investigates how companies may adopt graphic and logos so as to make them appear more green and environmentally friendly. We are currently seeking an undergraduate research assistant to assist with scraping logos from an online database.
Python and HTML knowledge This work will be overseen by both Professor Almond and Victoria Li, a Columbia Masters student, whose email is the primary contact.

____________________________________________________________________________________________________

The following positions are now CLOSED. Please DO NOT contact these researchers about the positions:

 

Dongcheng Yang (PhD Student) – POSITION CLOSED
Credit Guarantee and Financial Misallocation in Japan
This project investigates the impact of Japan’s Credit Guarantee Scheme on financial misallocation. It examines how government-backed credit guarantees influence firms’ access to debt and equity, potentially leading to inefficient allocation of financial resources. By using empirical approaches that include instrumental variable analysis and difference-in-difference (DID), the study seeks to assess the broader economic implications of such policies.
The RA will primarily support data cleaning, data analysis, and literature review. The ideal candidate should be proficient in statistical software such as Stata and Python, with the ability to use ArcGIS being a plus. Japanese language proficiency is desirable for navigating local databases and literature.

 

Nikhil Basavappa (PhD Student) – POSITION CLOSED
Agriculture, Information, and Climate Resilience
Joint with Ricardo Pommer Munoz (6th year PhD student). We have multiple projects examining how farmers in India can adapt to climate shocks. Our primary project examines how a large groundwater management scheme impacts productivity, whether the program helps farmers bear climate shocks, and whether information provision can complement both channels. Satellite projects include a study on how social cohesion impacts information diffusion among farmers and a study on how risk mitigating measures impact farmers’ demand for information.
We’re seeking RAs with good communication skills who are open to all parts of the research process, ranging from literature reviews to coding tasks. While coding skills aren’t strictly necessary (and there will be lots of learning on the job), some basic knowledge of R will be helpful, and proficiency is even better. Knowledge of Python and/or Javascript may also come in handy.

 

Anna Papp (PhD Student) – POSITION CLOSED
Climate Adaptation, Risk Shifting, and Digital Platforms
The RA will help with a project on climate adaptation in the food delivery industry. The RA’s primary tasks will include background research and data gathering related to the Mexican food delivery industry. For example, the RA will help with contacting companies/NGOs active in the food delivery industry for background info, help write a summary of the Mexican food delivery market, collect relevant news reports, and analyze labor force surveys. Depending on interests and skills, the RA may also help with data cleaning, processing, and econometric analysis.
Fluency in Spanish is required. Experience with R may be helpful, but is not required.

 

Clara Berestycki (PhD Student) – POSITION CLOSED
Climate Policy Uncertainty – Behavioral Adaptation to Pollution
We measure and study the impact of Climate Policy Uncertainty on Firm and Investor Behavior. We created an index measuring Climate Policy Uncertainty using newspaper data, and we study how firm investment, firm patenting activity, and stock market outcomes respond to changes in this type of uncertainty. We find that in general climate policy uncertainty has a negative impact. I am also working on a different project on behavioral adaptation to air pollution using cell-phone mobility data. We use this incredibly rich dataset to understand how individuals change their behavior when a pollution shock hits.
The tasks for the RA would be data collection and data exploration, and perhaps some literature review. I don’t require a specific coding language, but familiarity with a coding language like R, Python, or STATA, and some experience with data manipulation. For instance I could ask the RA to collect some data online and then produce descriptive statistics on that dataset.

 

Fanyu Wang (PhD Student) – POSITIONS CLOSED
1) Effects of environmental information disclosure on property price and avoidance behaviors
Starting on October 16, 2024, all public water systems must comply with EPA’s 2021 Lead and Copper Rule Revisions (LCRR), The LCRR requires notification to persons served of known or potential lead service line and Tier 1 public notification of a lead action level exceedance. This project aims to investigate the effects of the newly disclosed information about lead service lines, especially on housing prices and residents’ behaviors to avoid exposure to lead contamination.
The primary tasks include background research and survey design and distribution. The RA may also help with data collection, cleaning, and processing. The survey is to compare residents’ beliefs and behaviors before and after receiving the new information. Experiences with surveys are a big plus. Experiences with R, Python, or Stata can be helpful, but no required.

2) Effects of signals of electricity service reliability on property price and adaptive behaviors
The power outage events in Texas in February 2021 and the consequential state senate bill to improve grid reliability created salient signals about electricity service reliability, This project, conducted in collaboration with Professor Douglas Almond and Professor Stephen Puller, seeks to investigate the effects of these signals on housing prices and users’ adaptative behaviors.
The RA’s primary task include background research and data collection, cleaning, and processing. The data would involve power grid topology, power outage, solar panel installation, housing prices, etc. Depending on interests and skills, the RA can also participate in econometrics analysis. Coding experiences are required, preferably R or Python but Stata is helpful too.

 

Zikai Xu (PhD Student) – POSITION CLOSED
Cheap Talk in Search Markets
We study a model of search market where a consumer can only acquire information via cheap talk by searching a seller. We characterize the set of symmetric perfect Bayesian equilibria and the consumer-optimal equilibrium. We also provide a mechanism without transfers to implement the consumer-optimal equilibrium.
Search and read related literature. Familiar with LaTeX (Overleaf preferred).

 

Gina Markov (PhD Student) – POSITION CLOSED
Determinants of Technological Innovation
This project involves looking at the determinants of technological innovation in the US. This involves obtaining historical data on patents, funding of research and development, and corporate lobbying. The goal is to assess the historical incentives underlying automation and other types of technical change, and how they relate to the future of AI in the labor market.
The main tasks will involve data processing of different types of datasets (patents, etc.), as well as applying replication packages of previous papers to new datasets. Data summary/analysis of these datasets in either R or Stata is desired. Ability to do basic machine learning or NLP would be ideal but not required, since we will be working with text data.

 

Kamelia Stavreva (PhD Student)  – POSITIONS CLOSED
1) Historical Skin Color Project
This project uses historical data to study gaps across a variety of outcomes (such as income, migration, homeownership, and occupation) between individuals with different skin colors. The project currently focuses on differences for Black people and asks why these differences emerge, how they impact their lives, how these impacts transmit over generations, and how they have changed over time. The project also examines how these skin color differences relate to broader changes in racial inequality over time. A research assistant will help analyze and work through a large set of historical data from the late 1800s to the present day.
We are looking for applicants that have experience using languages such as STATA or R and are able to assist in working with big data or survey datasets. Any prior experience with coding languages is a plus. Tasks may also include literature reviews, analysis, and looking through historical texts.

2) Privatization of misdemeanor supervision in Florida and impacts on reintegration
This project asks, how does a county entering or exiting private misdemeanor probation in Florida impact reintegration of convicted individuals supervised by that county? Does contracting out an important part of the criminal justice system change the incentives of the system? It will examine the impact on individuals in particular looking at if it changes recidivism. I.e. Are private probation companies more or less likely to give out non-crime related (technical) violations to misdemeanants than government-run probation offices? Also, it will look at the impact on the criminal justice system. For example, does using a private probation company change judge sentencing decisions? Do judges now take on the incentives of the probation company?
I am looking for students that are familiar with working in STATA as well as able to do tasks like conducting literature reviews and analyzing data. Familiarity with econometric methods and economic analysis is a bonus.

 

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.
The RA would need to be reasonably familiar with Python and Stata, and will need to be able to learn independently and proactively. At the minimum, the RA will need to help me run and monitor some scripts that I write (data scraping, etc), check my code, write documentations, and raise questions if you see something not making sense. If you can and want to program more and participate more in the design of the project, that’ll be great!

 

Patrick Farrell (PhD Student) – POSITION CLOSED
The Boroughs Were Burning
The 1960s and 1970s were marked by a sharp rise in destructive urban fires in many U.S. cities. Some neighborhoods in the South Bronx lost upwards of 90% of their housing stock during this period. These fires have been attributed to the consequences of disinvestment and intentional arson. This project aims to create a database of the fires, drawing on FDNY records, and study their impact.
Familiarity with Stata and with GIS software (ArcGIS or QGIS)

 

Waseem Noor (Professor) – POSITION CLOSED
1) Global Economy Course Update
The Global Economy course will be taught in Spring 2025. This project will create some mini case studies 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 review the weekly readings and update them. The RA will also help with suggestions for future questions on the exams.
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.

 

Catalina Gomez Colomer (PhD Student) – POSITION CLOSED
Health and Public Economics
I’m currently working on projects related to health and public economics with data from Chile. Related to health economics I want to answer: how can we reduce healthcare waiting list in the public system? Under what conditions are nurses substitutes of doctors? Related to public economics I’m interested in answering: Who becomes a public employee? What incentives are key to attract the “right” people?
Read and summarize economic papers. Read and summarize real world data, policy reports, etc. You will be helping me better understand the context and literature of the topics I’m studying. Coding (in Stata or R) is not likely to be required but I’m open to it if there is interest from the RA. Applicants that speak Spanish are encouraged to apply as I’m working in the Chilean context. But Spanish is not required.

 

Eshaan Patel (PhD Student) – POSITION CLOSED
Power, Targeting, and Firm Growth
There are dramatic differences in institutions and power across countries. In a context with weak institutions, are powerful firms able to use the political sector to target their less powerful competitors? This project seeks to identify the implications of this channel using data from Latin America to see if it can explain aggregate data on firm size and growth. RAs will have the opportunity to develop skills in applied economic research and data analysis more broadly.
Tasks include: a GIS task matching firms’ addresses to map coordinates (latitude and longitude) using the proximity toolset of ARCGIS or additional tools; digitizing political contributions data from PDF format to CSV. Tasks require basic knowledge of Spanish. Prior GIS experience or digitization experience is useful but not required.

 

Dafne Murillo (PhD Student) – POSITION CLOSED
Land Redistribution and Productivity: Evidence from Peru
The project investigates land reform in 1970s Latin America. 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. The study aims to analyze the impact of property rights redistribution on productivity and welfare.
RAs will have the opportunity to develop skills in applied economic research and data analysis. The duties involve project management, data cleaning, and compiling a unique dataset from various historical sources. The comprehensive datasets are then analyzed using Stata, especially in the study phase delving deeper into the econometrics data analysis, identification design and interpretation of results. Knowledge of Spanish is preferred. Knowledge of Stata, GIS, and/or Python is useful but not required.

 

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: cleaning and classifying information collected from job seeking students’ resumes and 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, especially around the earlier part of the semester. Knowledge of Stata and R would be a plus.

 

Donato Onorato (PhD Student) – POSITION CLOSED
The Nature of Firm Lobbying
The lobbying industry in the United States is large, and the origin of these lobbying revenues are often firms and industry-associations. Given the size of the lobbying industry, one immediately wonders whether lobbying is distortionary. This project aims to use historical data from lobbying reports in post-war (1946-54) U.S. along with recent advances in natural language processing to understand how firm lobbying behavior shapes important policy outcomes including the effectiveness of industrial policy.
Research assistants will serve a crucial role in helping us digitize and construct a database of historical firm lobbying. Tasks may include helping with cleaning and post-processing of AI generated output from lobbying reports; helping with coding tasks, data cleaning, and data validation for the creation of a novel firm lobbying database. All experience levels are welcome.

 

Kathryn McDonald (PhD Student) – POSITION CLOSED
Endogenous Production Networks and Trade Shocks
This project studies the restructuring of global supply chains using a novel dataset on buyer-supplier relationships for consumer retail goods. The goal of the project is to investigate the stickiness of firm-to-firm relationships and the role of bargaining power in the supply chain adjustment to shocks. The project would require 2 RAs for data cleaning tasks and data analysis. RAs should have strong skills in Python or R, and experience working with large datasets. Knowledge of Stata is useful, but not required.

 

Kate Kennedy-Moulton (PhD Student) – POSITION CLOSED
Exploring Factors Affecting Vasectomy Utilization
Sterilization is a safe, effective, and widely-used form of contraception. Although male sterilization is cheaper and safer than female sterilization, it is much less prevalent. According to the 2013 – 2015 National Survey of Family Growth, about 22% of women aged 15-44 have had a sterilization procedure compared to 5% of all men aged 15-44 [KFF]. To investigate factors influencing vasectomy utilization, I plan to examine several potential channels: insurance coverage, access to abortion, child support laws, and social norms.
Researching and compiling state-level law changes, literature review

 

Martín Uribe (Professor) – POSITION CLOSED
Capital Account Restrictions: A New Perspective
Professor Uribe is currently seeking research assistants (RAs) under the Economics Department’s undergraduate research assistant program. These RAs will collaborate with a team comprising researchers from Columbia and the International Monetary Fund (IMF). The primary responsibility involves gathering information on global capital-control measures, utilizing various sources and techniques. The search is particularly targeting, but not exclusively limited to, students possessing skills in Economics and computer sciences.
Economics, data skills, data management, international macroeconomics

 

Hannah Solheim (PhD Student) –  POSITION CLOSED
A Study about Social Media Algorithms
This project is joint work with Nancy Wang (MIT). We are currently conducting a pilot experiment to investigate how social media algorithms influence the content that users see. Additional information about the project is available upon request.
The RA will have a variety of tasks, which may include: experiment prep, literature reviews, and data analysis. Knowledge of STATA is a plus, but not required. RAs may also be asked to work on other projects broadly related to behavioral and applied microeconomics.

 

Tianhao Liu (PhD Student) –  POSITION CLOSED
Correlation Ambiguity and Information Overload
This project studies how the decision-maker will behavior if he/she is uncertain about the correlation structure of the signals and ambiguity-averse. We will explore the value of acquiring multiple signals for such a decision-maker. We may also touch on other projects related to information and contract theory.
The RA will help proofread the draft, check proofs and solve/find examples. Strong mathematical and microeconomic theory background is needed for this position (especially probability theory). Interest in microeconomic theory research is encouraged. Basic programming skill may be needed to conduct numerical computations (solving equations, running simulations, etc.).

 

Kosha Modi (PhD Student) – POSITIONS CLOSED
The perceived sources of unexpected inflation
We use high-frequency asset price changes around Consumer Price Index announcements in the US to learn about market perceptions regarding the economy. First, we document some facts. An unexpected increase in the CPI inflation leads to an increase in (a) treasury nominal yields (b) forward breakeven inflation rates. The price of S&P 500 and the future annual dividends of S&P 500 companies might increase or decrease in response to the surprise. We interpret these facts through the lens of a New Keynesian Model with an inflation announcement to decompose unexpected inflation into demand and supply components. We find that the share of supply in unexpected inflation has increased by 10 percentage points post-covid.
STATA

 

Kate Musen (PhD Student) – POSITIONS CLOSED
Child Health and Welfare Policy in the United States
I am looking for up to two RAs to assist with multiple projects in the domain of child health and welfare policy in the United States. Topics of study include foster care reform, changes to the Medicaid program, child mental health, and historical determinants of infant health. This project is ideal for students looking to learn more about applied microeconomics research and child welfare policy. Interest in these issues is more important than advanced technical skills.
Potential tasks include literature reviews, compiling the details of relevant policy changes, background research, and data entry. Knowledge of Excel is necessary. Knowledge of Stata and of Wayback Machine is a plus but not required. If the RA is proficient in Stata, I may also ask for assistance with code review. Attention to detail, organization, clear communication, and tenacious Googling are the most important skills for this project.

 

Abhishek Deshwal (PhD Student) – POSITIONS CLOSED
1) Market Distortions and Environmental Externalities: Evidence from Energy Sector in India
Pre-existing market distortions may exacerbate pollution related externalities and lead to suboptimal environmental policy. This project investigates this interaction in the context of thermal based electricity generation in India, a sector that accounts for 40% of total carbon emissions in the country and 3.5% of emissions globally. Exploiting rich data, the project shows a bias towards coal plants that are old, obsolete and more polluting than the cleaner and more efficient newer vintage plants (mostly privately owned) built in the past 15 years. Then, it shows that market failures in the supply of coal are a major cause of this inefficiency – public power plants get secure access to cheap subsidized coal while private power plants are forced to procure from markets at a premium that is often twice the price public plants face. Finally, the paper estimates the hidden economic and environmental costs of coal subsidies and compares the efficacy and optimality of alternative policies, including an optimal carbon tax.
The RAs may be assigned a range of responsibilities depending on skill, including: – Data cleaning and analysis (Stata/Python) – Coding linear constrained optimization problems in Python – Digitization of files using programming tools Familiarity with a coding language such as Stata or Python will be useful though not necessary.

2) Energy Policy, Groundwater Extraction and Adaptation to Climate Change
In India, unlike most parts of the world, energy, agriculture, and water operate at a nexus. This research aims to perform a rigorous evaluation of various energy policies adopted by the government, focusing on electricity consumers in the agricultural sector. Specifically, using quasi-experimental methods, this project seeks to analyze farmer responses to policies like Kisan Suryoday Yojana (KSY), that shifted electricity supply hours to daytime for increased utilization of solar energy, and PM-KUSUM, a scheme for solar-driven irrigation pumps. The outcomes we are interested in include the adoption of solar irrigation systems, water consumption through more efficient use of groundwater, and agricultural incomes. Additionally, we will estimate the high-level effects of these policies on aggregate electricity consumption, the composition of the energy mix, and aggregate reductions in carbon intensity.
Tasks vary by skill of the RA and include:

• Data cleaning and analysis
• Fuzzy matching datasets
• Running basic regressions

Familiarity with languages such as Stata and/or Python will be useful though not necessary.

David Weinstein (Professor) – POSITION CLOSED
The Impact of WWII on Militarism and Growth
The RA will help with two projects. The first seeks to explore the political economy of massive Japanese civilian and military casualties on postwar Japanese attitudes of survivors towards militarism. The second examines whether and how US military patents issued during World War II affected global economic growth.
The RA will help build datasets needed to investigate these topics. Knowledge of Japanese is not necessary, but applicants who speak the language should indicate it. Knowledge of econometrics and programming in languages like Python and Stata will be a major asset. Applicants should send a copy of their transcript.