Undergraduate Student Researcher Mentoring Program

We believe that conducting research is an important part of your training as an economist. Learning how to define a question, locate and review related literature, identify, download and clean data, and conduct empirical analysis develops a skill set highly valued by graduate programs and future employers alike.  The Economics Department has two programs: [1] the general undergraduate student researcher program, and [2] the Lynde grad student mentoring program.  The mentoring program is a subset of the more general program.  You sign up only once. . . Read on.

The undergrad student researcher program is designed for Economics majors at any stage of your education.  If you have not yet taken econometrics -- which Prof. Olney says you should take as soon as you can! -- we still encourage you to apply.  Some graduate students or faculty need RAs who can do coding in Stata or R or Python, but others are looking for RAs to do literature searches or other tasks that do not require econometrics or CS/DS toolsets. 

The grad student mentoring program adds in several components that ensure the undergraduate student researcher experience provides you not only with an experience to list on your resume, but also with a graduate student mentor who will teach you about research and who is available to discuss courses, work or graduate school plans, the life of an economist, and whatever else may come up.  The mentoring program is funded by a generous donation from Cal alumnus, Dr. Matthew Lynde. 


About the Lynde Mentoring Program
The features of the mentoring program are listed below. 

  • You work with a graduate student who has expressed interest in and received training in serving as a mentor for undergraduates.  Mentoring means that the graduate student has made a commitment to discussing the research process with the RA, helping the RA see the big picture for the research project and the specific tasks the RA is working on, talking with the RA about future opportunities in economics or in research (including graduate school options), and ensuring that the RA acquires research skills as part of the RA process. If you are considering graduate school in economics, or just want to know more about what it means to be an economist, the mentoring program may be for you.
  • A welcoming reception (dinner provided) for all RAs hired as part of the Mentoring Program will be held on Tuesday evening, February 11, 6:00-7:30, in 648 Evans. Food will be provided.  The welcoming reception will give you the opportunity to meet all the other undergraduate RAs serving this term, learn about all of this term's projects, and ask questions about research in economics.
  • A Facebook site for Economics undergrad RAs lets you keep in contact with each other throughout the term and beyond. Facing a coding challenge? Post a question on the site. Having trouble downloading data or articles? Post a question on the site. Wanting to exchange information about post-graduation or summer research opportunities?  Post to the site. RAs from previous years continue as members of the site, allowing the possibility of networking with recent alumni.
  • A pair of workshops conducted by Economics graduate student Isabelle Cohen will offer you tips & training in the use of Stata and LaTeX. Beginning Stata workshop is Friday Feb 14, 11-1. Advanced Stata workshop is Wednesday Feb 19, 4-5. LaTeX workshop is Wednesday Feb 19, 5-6. More information will be on the RSVP form for the welcoming reception.
  • An end-of-term poster reception (dinner provided) scheduled for Tuesday evening April 28, 6:00 - 7:30 pm, 611 Evans (Peixotto Room) at which you and the grad student you're working with will display a poster that describes the project and the work you've contributed to the project. Posters are on display in the 6th floor of Evans Hall for at least a semester following the reception.
  • As an alternative to the end-of-term poster session, you can instead (or also) attend and display your poster at the department's Cal Day event on Saturday April 18 at which we will have some of the research posters on display and you'll have opportunities to talk with prospective Cal students and their families.
  • A small financial incentive ($50) will be paid in May to undergrad RAs who participate in the mentoring program by working with a grad student mentor, attending the welcoming reception on February 11, and attending either the Cal Day event on April 18 or the poster session on April 28.

There are about 40 graduate students who have completed the training to serve as mentors.  Their projects cover a wide range of fields and the research tasks they are looking for help with also cover a wide range. The second column of the table below indicates whether or not the grad student is part of the mentoring program. If you are interested in participating in the mentoring program, be sure to check the appropriate box at the bottom of the application for serving as an undergrad RA.

There are also Economics and BPP (part of Haas's PhD program) grad students who are not part of the mentoring program, postdocs, and ARE & Economics faculty who will look at the applications in order to find RAs.  So you can be an RA without being in the mentoring program.


About the Application
The application form for undergraduate RA positions is available at  https://www.econ.berkeley.edu/undergrad/economics-majors-interested-ra-positions.  The Economics faculty and graduate students seeking RA assistance will reach out to those students they are interested in interviewing.  Watch your email!

On the application form, you can signal up to four (4) projects that particularly interest you.  Use the project number in the left most column when completing the "signalling" part of the application. The second column tells you whether or not the person in charge of the project is a faculty member or a graduate student who is part of the Mentoring Program.  


About Earning Econ 199 Credits
An important point about compensation: Being an RA for a graduate student or faculty member is considered an educational or academic endeavor. In most cases, these are unpaid positions, much like an academic internship. You must be an enrolled student. For Summer RA positions, enrollment in summer or fall suffices.  Due to labor laws, we cannot allow people who have already graduated to serve as an unpaid RA. You can receive Econ 199 credits for being an RA. These will be P/NP credits that count toward graduation but not as an upper-division elective. 


Non-Economics Faculty & Graduate Students Seeking RA Assistance
Graduate students or faculty from other departments can also hire our Economics undergraduates! We invite grad students, post-docs, and faculty who are not in the Economics Department to submit a description of their position directly to the undergraduate office (ugrad@econ.berkeley.edu) for inclusion in the weekly bCourses e-blast that goes to all Econ majors. Please include the following information: who you are, contact information, deadline for applying; title & description of the project; expected RA tasks and anticipated RA skill set; whether compensation is $ or units; anticipated # of hours per week. Send your info by email to ugrad@econ.berkeley.edu with an indication that it is for the weekly e-blast to Economics majors.


List of Projects for this Term

Projects for Summer 2020

 

 

Project # In Mentoring Program? Grad Student or Faculty # of RA's needed Project Title Project Abstract RA tasks
1   Faculty + Grad Student 2 new Which Researchers Care Most About Magnitude and Precision? Revelations from Abstracts Empirical studies typically estimate the effect of one thing (perhaps class size) on another (perhaps earnings). Abstracts report what researchers take to be their important findings. Unfortunately, abstracts often only report the sign and statistical significance of an effect rather than the magnitude of the effect and how precisely that magnitude is estimated. Our project investigates how economists report the magnitude and precision of their empirical findings compared to other social science and science disciplines (including psychology, political science, sociology, and medicine). We will also study how much more or less papers reporting magnitudes and precision are cited more in academia or get more press coverage (e.g., papers that report that “10% smaller classes raise lifetime earnings by $300,000 +/- $50,000” rather than simply reporting that “smaller classes increase earnings.”) The RA will have the opportunity to read and evaluate abstracts across a variety of fields and disciplines. The RA will also help record citation counts and quantify press coverage of journal articles. Depending on the progress of the project and the interests of the RA, some statistical analysis may be possible as well.
2   Econ grad student 4 new Television Exposure of Vietnam War Content and its Effect on True Volunteer Enrollment Among Vietnam War Veterans I aim to explore how exposure to Vietnam War related content via television networks, if any, affected the enrollment of true volunteers during the Vietnam War. Digitization of Television Factobooks, Data Cleaning through STATA, Classifying CBS, NBC, and ABC television content to Vietnam War related variables of interest.
3   Econ grad student 2 new Payroll Taxes and Pass Through to Labor Market Merging Brazilian IRS data with RAIS, I intend to analyze the tax incidence of a billionaire tax cut on payroll taxes implemented in Brazil. This reform happened between 2012 and 2018 and targeted corporations in a number of pre-determined sectors. This research will add to the existing literature on Public Finance by providing a clear scientific understanding of corporate tax incidence, which has not been attempted by previous studies. It also aims to understand the labor market impacts of such policies, in terms of employment and wages. I am also interested in studying rent sharing among entrepreneurs, high-skilled and low-skilled workers. Finally, the asymmetry of firms' responses to subsidies - when the incentive was first conceived vis-à-vis when the Government was phasing it out - is another interesting aspect to analyze. Cleaning data set, downloading data and exploring econometrics techniques
4   Econ grad student 2 new The Social Cost of Informality: An Optimal Taxation Approach Growing up in Brazil, I have witnessed first-hand the havoc that government mismanagement can cause to the economy. The Brazilian economy, like that of many other developing economies, is particularly plagued by informality. To avoid high levels of taxation and burdensome government regulation, many economic agents flee the formal job market and take refuge in sectors outside the Government’s reach. I want to discuss and analyze the causes and effects of this job market informality. Cleaning data set, downloading data and exploring econometrics techniques
5 yes Econ grad student 2 new Foreign Monetary Shocks through Multinational Enterprises The past two decades have witnessed the establishment of global value chain. With it, comes a rapid expansion of multinational enterprises (MNEs) and their production network. Even though the activities of MNEs have since been a heavily debated topic, their impacts have been hardly measured. In this project, I aim to link official records with detailed firm-level data to investigate whether MNEs can propagate or mitigate the transmission of foreign price shocks to an economy, and whether they can challenge or enhance a country’s monetary autonomy in the medium- or long-run. Based on the results of initial findings, I will analyze whether a monetary authority can disproportionally benefit domestic exporters through devaluing its currency and the welfare effects of such policy on domestic consumers. (1) Candidates with a CS background in natural language processing or name matching are preferred, though these skills are not required. The current problem on hands involves matching two databases by firm names with equivalent but different spellings and/or spelling errors.
(2) Most of the time, you will help me update a private database using multiple data sources. Being able to pay attention to details and keep data well-organized are thus crucial for the project’s success.
(3) Occasional data cleaning in Stata or Excel as well as performing preliminary analysis.
(4) Preferred skills: Stata, Excel, natural language processing in Stata, Python, or other software.
(5) Preferred background: International trade, finance, and macroeconomics (Taylor role and monetary policy).
6 yes BPP grad student 2 new Revisiting the Glorious Revolution: Inclusion or Elite Persistence? England after the Glorious Revolution of 1688 is widely regarded by economists as the archetypal example for how inclusive institutions enable economic growth. Yet, there is very little empirical evidence of greater access to power or inclusion of new societal actors after 1688. We plan to empirically examine whether there was greater inclusion in England post-1688. If England was, indeed, more inclusive, we would expect to see more individuals from different backgrounds (i.e. entry) among the political elite. Our main data on England’s political elite consists of over 52,000 biographies of individual members of the United Kingdom’s House of Commons between 1386 and 1832. We are in the process of using natural language processing and machine learning to classify parliamentarians as members of the old elite (nobles, land owners, etc.) or entrants from new social classes (e.g. merchants and overseas traders). Our goal is to match RAs to tasks based on interest and skills. We expect RAs to mainly contribute to the empirical and data-intensive aspects of the project. We use Python, R and Stata. Tasks include, for example:
1) Collecting and digitizing novel archival data
2) Web scraping and Optical Character Recognition of historical records
3) Combining data from multiple sources to construct new data sets
4) Working with “text as data” using machine learning and natural language processing
5) Analyzing the data using econometric methods
6) Visualizing the results in graphs and maps
7 yes BPP grad student 2 new Market Integration and Intergenerational Welfare: Evidence from 19th Century Railroad Expansion We study how market integration can create winners and losers across generations. Market integration can have intergenerational effects either directly by shifting children’s returns to skill and by increasing their opportunities to migrate, or indirectly through their parents’ income. Can these effects compensate for potential losses of parents? Alternatively, do gains and losses persist - or even compound - across generations? To answer this question, we look at the intergenerational effects of railroad expansion in the 19th century United States. This setting allows us to combine substantial variation in market integration with matched father-son outcomes from restricted access full-count census data. We are building an empirical spatial model to interpret the impact of market integration, to separate the channels through which it affects both generations, and to evaluate implications for welfare. We also plan to look at political economy effects by analyzing votes for the Populist Party candidate during the 1892 presidential election. To isolate plausibly exogenous variation in market integration, we plan to instrument actual railroad construction with predicted railroad construction from a model of optimal infrastructure investment. Our goal is to match RAs to tasks based on interest and skills. We expect RAs to mainly contribute to the empirical and data-intensive aspects of the project. We use Python, R, and Stata. Tasks include, for example:
1) Collecting and digitizing novel historical data
2) Working with geo-spatial data and digitized maps
3) Combining data from the census and other sources to construct new data sets
4) Analyzing the data using econometric methods
5) Visualizing the results in graphs and maps

RAs with an interest in theory are welcome to contribute to the modelling component of the project.
8 yes BPP grad student 3 new Replacing the ties that bind: Welfare State Expansion, Mobility, and Modernization To what extent did the expansion of the welfare state contribute to economic modernization? In theory, when the state takes over services like old-age support, this could free up family members that would have had to provide these services and enable the next generation to move to new regions and new economic sectors. I test this hypothesis using the 1890 Dependent and Disability Pension Act as a natural experiment. The 1890 Act transformed the Union Army Civil War pension into the United States’ first federal old-age support. Using restricted-access full-count census data, I match sons of Union veterans from 1870 to their records in 1880, 1900, and 1910. I provide Difference-in-differences estimates on sons’ decisions to cohabit with their fathers, to leave farming, and to move to urban areas. The goal is to match RAs to tasks based on interest and skills. I expect RAs to mainly contribute to the empirical and data-intensive aspects of the project. We mostly use Python, R, and Stata. Tasks include, for example:
1) Collecting and digitizing novel historical data
2) Web scraping and Optical Character Recognition of historical records
3) Working with geo-spatial data and digitized maps
4) Combining data from the census and other sources to construct new data sets
5) Analyzing the data using econometric methods
6) Visualizing the results in graphs and maps
9 yes BPP grad student 3 new Organized Redistribution: Can Political Machines Promote Social Mobility? Political machines are hierarchical organizations with a dense network of local brokers that mobilize votes for their candidates with promises of patronage, pork, or other rewards (e.g. outright vote buying) and threats. Machines dominate elections in many developing countries. Political machines and their clientelistic practices are commonly associated with corruption and bad governance. Existing research emphasizes how brokers often target poorer voters. But we know little about the impacts of machine politics on social mobility. By targeting patronage and public services at poorer citizens, do machine politicians contribute to more equal outcomes? Can disenfranchised groups like immigrants or minorities improve their situation by rising through the machine hierarchy? We study these questions in the context of the archetypical machine in US history: New York City’s Tammany Hall. Combining individual-level census data with data on the machine’s personnel and novel information on patronage appointments, government contracts and local public good provision, we document who profits from machine politics. The goal is to match RAs to tasks based on interest and skills. I expect RAs to mainly contribute to the empirical and data-intensive aspects of the project. We use Python, R, and Stata. Tasks include, for example:
1) Collecting and digitizing novel historical data
2) Web scraping and Optical Character Recognition of historical records
3) Working with geo-spatial data and digitized maps
4) Combining data from the census and other sources to construct new data sets
5) Analyzing the data using econometric methods
6) Visualizing the results in graphs and maps
10 yes Econ grad student 4 new Unpacking Intergenerational Immobility: parents' influence on students' career choices In many countries, we observe relatively low levels of intergenerational mobility. Why is there such a strong relationship between family background and children's educational and career choices (and outcomes)? In a field experiment in collaboration with high schools in Germany, I document students' and parents' career aspirations and examine to what extent students adjust their career aspirations and choices to their parents. Are parents' preferences, beliefs and expectations driving students' aspirations and choices beyond any differences in financial resources and thus, an important explication behind persistent differences in career choices across socio-economic backgrounds? This summer, I'll be mainly focused on analyzing the data from two different sources (my own experiment and a separate German dataset) and writing up the results. I'll be needing help with a variety of tasks:

- Data cleaning (e.g. combining several survey waves to analyze long-term consequences of following your own or your parents' aspirations)
- Data analysis
- Data visualization (e.g. work on graphs to present results)

Some knowledge of STATA (or Python) would be a big plus, a lot of your tasks will probably involve learning by doing.
11 yes Econ grad student 1 new Drinking your social image: champagne consumption in nightclubs How much are people willing to pay to signal status/show off? Using champagne consumption in nightclubs, I estimate people's willingness to pay. While I already have data on bottle prices in nightclubs, I am still looking for some consumption/sales data from night clubs (or from retailers). If you have i) any idea how to obtain some data (even in creative ways), ii) any relations to club-owners (or someone selling champagne to clubs, or anyone who could have access to data), please apply! I'd be super happy to explore this data source together!
12 yes Econ grad student 2 new Motivated Memory when Reflecting on Big Life Decisions How do individuals and societies learn about long-term processes unfolding over many years? Memory and retrospection are arguably key to individual and social learning over time, but remain under-explored. In a dataset of 5,000 Kenyan women and men, I find that reproductive realizations often deviate from their initial desires. Individuals' memory of this, however, is imperfect and biased, at least partly so for motivated reasons. Motivated memory is consequential: among those with more children than initially desired, those who do not recall this "excess fertility" would recommend the next generation to have more children and to get married earlier, invest less in contraception and are less favorable to family planning policies. Motivated memory may thus play a role in cultural persistence, in this instance of perpetuating high fertility. I'll be working on writing up a first paper draft around the key results so far and will thus need help with the following tasks:

- data visualization (trying to improve Graphs, ideally making them perfectly drive home the key results/messages)
- proofreading of individual chapters/ the whole paper: catching typos, is everything understandable, succinct and short enough?
- maybe: some additional data cleaning and data analysis

some knowledge of STATA (or Python) is a plus, otherwise most learning will probably simply come in the form of learning-by-doing
13 yes Econ grad student 1 new Identity, belief formation and investment behavior In what ways does identity shape our daily decisions as well as the big decisions in our life? Offering respondents bets - among others on the presidential election and soccer games - as investment opportunities, we examine how social- and self-identity affect individuals' investment behavior and through which channels it does so: does our identity make us overconfident and interpret news in motivated ways? Or does it prescribe strong norms that are costly to violate? After first estimating the price tag people put on their identity, in a second step we try to disentangle different components driving this effect. This summer, we will be running the first pilots collecting data from several hundred respondents. We will need help with survey design and getting the survey started. You don't necessarily need any specific prior knowledge, but should be willing to learn by doing and figure out how to use Qualtrics.

In addition to survey design, we might also need help with some simple data cleaning, data analysis and data visualization (ideally using either Stata, Python or R).
14   Econ grad student 2 new Illegal Markets and Government Capacity in Latin America In this project, we study how illegal activities and markets affect local government capacity in Latin America. We study several measures of government capacity such as tax collection and delivery of public goods, and the effects that increased presence of illegal activities has on these. RAs are expected to clean and merge a number of datasets that we will provide. It is required that RAs have some knowledge of Spanish.
15 yes Econ grad student 1 new Evaluating the Impacts of the US Opportunity Zone Program We study the short-run impacts of the U.S. Opportunity Zone (OZ) program, a federal place-based policy that provides capital gains tax incentives for investments in more than 8,000 low-income census tracts. We use the universe of federal tax records and several complementary identification strategies to estimate the causal effects of OZ designation on tract-level investment, employment, wages, poverty, migration, and local prices. Qualitative research on institutional details -- e.g. how did states choose which neighborhoods would be designated as Opportunity Zones? What were the economic and political criteria? Basic quantitative research skills -- such as producing summary statistics, basic regressions, an cleaning data -- are a plus. We look forward to mentoring a student about the research process and investing in a student who is eager to learn new quantitative and qualitative research skills.
16   Haas BPP PhD student 1 new The Impact of privatization on health delivery in Brazil I'm studying how the decision of local (municipal and state) government to “privatize” the provision of health affects the quality of service delivery. My setting is Brazil, which provides all citizens with free, universal health care, but of varying quality. In order to improve the services, several governments contract with firms and non profits to operate local clinics and hospitals. I’m using very rich data on health personnel and procedures to investigate the causal impact of privatization on service quality.
The main task of the RA would be to collect, organize and clean data on health establishments, personnel and procedures. All data is public and I have started working with it, so I would provide the RA with preliminary codes. Knowledge of coding in R is preferred and knowledge of Portuguese or Spanish is big advantage but not required. If the RA speaks either of those languages the project would also involve some research documenting privatization events.
17   Econ grad student 1 new Land Reform and the Taiwanese Miracle In the 1950s, Taiwan enacted one of the most extensive non-communist land redistributions in East Asia, with over 71% of rented land redistributed to landless tenant farmers. We are studying the effect of land reform on Taiwan's "miraculous" transformation -- from a poor, mostly agrarian society, to a rich manufacturing hub.
We need help with a variety of data and translation tasks. These include digitizing historical records, translating historical documents, and reading the Chinese-language economic literature. Knowledge of Mandarin Chinese essential, experience with Python a plus.
18   Econ faculty 2 new Long lasting effects on prior lifetime experiences, with application to COVID-19 and other pandemic experiences, to the role of gender differences in physicians behavior, and the belief formation of investors. I will be pursuing one or more projects that explore how prior lifetime experiences can have longlasting effects on individual risk-taking and decision-making. One application will be exposure to a pandemic such as COVID-19, though we will look for data of other pandemic experiences; others relate to traditional gender roles and investment behavior.
Identify the existence of data sets; obtain access to data; clean; design data base; estimate empirical models (if able to); learn about laboratory experimental design on belief formation elicitation; literature search and summary; discussion of possible research hypotheses.
19   Econ grad student 1 new Supply-side Shocks in a Monetary Union: Evidence from Fracking The goal of this paper is to test predictions of the RBC and New Keynesian frameworks about the behavior of the economy following a technology shock. We first identify local technology shocks occurring with fracking adoption. Subsequently, we provide cross-sectional evidence of the effect of fracking production and related TFP shocks on several macroeconomic variables. Then, we construct a two-region general equilibrium model of a monetary union, imposing key assumptions of either a standard Real Business Cycle or a New Keynesian model. Finally, we test the validity of alternative frameworks, and derive the aggregate implications under different monetary policy regimes.
Tasks for this project involve data collection and cleaning, modeling (if interested). Scraping abilities would be great. Use of Stata and Matlab is useful.
20   Econ grad student 2 new Capacity and Compliance: A Randomized Evaluation on Taxation in Uganda This project builds on a randomized control trial conducted last summer with the Uganda Revenue Authority which assesses how the framing of messages which encourage tax compliance matters for efficacy. We will combine data from the 100,000 small business owners enrolled in the program and national data on Uganda's health and education services in order to assess whether and how efficacy also varies based on what sort of services the individual is exposed to prior to payment.
Undergraduate RAs will be helping primarily with geocoding the locations of business owners, health centers and schools in Uganda, and ideally using that geocoded data for analysis. Either a hands-on or a programming-driven approach will be allowed; creativity (and diligence) will be essential.
21   Econ grad student 1 new Credit shocks’ and production network Do aggregate credit supply shocks induce inefficient production networks? To answer this question, first I build a model that allows for endogenous formation of production linkages to understand the financial and productivity forces at play in the determination of firm-to-firm matches when these face aggregate credit shocks. The model allows me to quantify to what extend the credit shocks contribute to an efficient allocation of inputs across the production network or the disruption of these.
(1) Data cleaning for a large dataset (2) Basic statistics and data visualization production for a large dataset. Strong programming skills in Python needed.


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Prepared by Martha Olney (olney@berkeley.edu)
Last update 5/12/2020 3:45 pm