Abstract
Learn how to turn messy digital-platform data into credible, publishable causal evidence. This PhD course studies marketplaces, social media, and search/streaming platforms, with a focus on how to find and justify identification in real platform environments. We start from the research question, i.e., defining the right estimand and stakeholder outcomes, and map it to feasible sources of variation, and the data needed to measure them. The course emphasizes modern DiD and event-study designs for platform policies, how to diagnose and stress-test them with falsification and robustness tools, and when (and how) to use experiments, accounting for interference and spillovers. By the end, participants will be able to (i) formulate platform research questions as clear causal estimands, (ii) build and defend DiD/event-study designs for platform shocks, (iii) evaluate platform experiments under spillovers and multi-sided responses, and (iv) use ready-to-adapt R/Python templates and credibility checklists to move from idea to a seminar-ready empirical design.
This online PhD course trains students to use online-platform data to answer causal questions about digital platform. We cover how to identify and measure shocks in platform settings (rollouts, ranking/recommendation updates, moderation/enforcement changes, pricing/monetization moves, and regulatory events), and how to analyze them using modern DiD/event studies and/or with experiments when randomization is feasible鈥攁ccounting for spillovers and marketplace interactions.
Teaching combines lectures with discussion of pre-assigned papers and hands-on activities (worked examples, design clinics, and structured peer feedback). Students are expected to prepare via readings before each session and learn between sessions through independent study, including optional walkthroughs of provided R/Python templates and brief reflective notes for their own research ideas (not graded).
By the end of the course, students will be able to:
- Translate platform questions into causal questions
- Identify credible sources of variation in platform settings and the data needed to study them.
- Implement and interpret causal inferences analyses for digital platform.
- Diagnose and strengthen causal claims using robustness checks suited to platform data problems.
Design and interpret platform experiments when randomization is feasible.
Session 1
- Goldfarb, A. & Tucker, C. (2019). 鈥淒igital Economics鈥, Journal of Economic Literature
Session 2
- Quinn, M., Godinho de Matos, M. & Peukert, C. (2023). 鈥淭he Welfare Effects of Mobile Internet Access: Evidence from Roam-Like-at-Home.鈥, The Economic Journal
- Sun, L. & Abraham, S. (2021). 鈥淓stimating Dynamic Treatment Effects in Event Studies with Heterogeneous Treatment Effects.鈥, Journal of Econometrics
Session 3
- Rambachan, A., and Roth J., (2023) 鈥淎 More Credible Approach to Parallel Trends鈥, The Review of Economic Studies
- Goodman-Bacon, A. (2021). 鈥淒ifference-in-Differences with Variation in Treatment Timing.鈥, Journal of Econometrics
Session 4
- Brynjolfsson, E., Collis, A. & Deisenroth, D. (2025). 鈥淭he Consumer Welfare Effects of Online Ads: Evidence from a Nine-Year Experiment.鈥, American Economic Review: Insights
- Peukert, C., Sen, A. & Claussen, J. (2024). 鈥淭he Editor and the Algorithm: Recommendation Technology in Online 美女福利电影院午夜. 鈥, Management Science
- Holtz, D., Lobel, R., Liskovich, I. & Aral, S. (2025). 鈥淩educing Interference Bias in Online Marketplace Pricing Experiments.鈥, Management Science.
Assessment
Assessment is based on active participation; students must attend sessions and complete the readings to pass.
Workload
Online synchronous: 10 hours, i.e., 4 sessions 脳 2.5 hours (lecture + discussion + activities/labs)
Asynchronous / self-study: 46 hours
- Required pre-reading (papers): 32 hours (assigned before each session)
- Independent study / consolidation: 14 hours (review notes, optional R/Python template walkthroughs, short personal reflection/design notes鈥攏ot submitted)
Attendance
Attendance is mandatory. The course certificate will be issued only to participants who have fulfilled all course requirements, which can include:
- Required attendance at the course sessions.
- Successful completion of the course assessments in accordance with the assessment criteria.
Contact
- Content related questions
Dr. Martin Quinn
Email address - Enrolment related questions
ERIM Doctoral Office
Email address
Register directly via the . If you have previously attended a course at 美女福利电影院午夜, you will already have an EUR account. If not, you will be asked to create one to complete your enrolment and receive access to course materials.
- Browse courses: Select the course that interests you and click on 'Enroll'.
- Create an account: Submit the details for your account. You will need it to access the course materials via the university鈥檚 learning management system.
- Complete registration: Fill out the registration form and submit payment.
- Confirmation: Receive a confirmation email with course details.
ERIM Full-time and Part-time PhD candidates as well as ERIM members can register free of charge via the university鈥檚 student information system, . A valid EUR student account is required to log in and complete enrolment.
If you encounter any issues accessing the course site, we recommend copying and pasting the link into an incognito/private browser window.
If you already have an Osiris account and encounter difficulties, please contact ERIM Doctoral office via summerschool@erim.eur.nl and they can assist by registering directly for your preferred Summer School courses.
Course fee: 鈧250 per EC credit
Courses are available free of charge for ERIM members and ERIM Full-time & Part-time PhD candidates.
After you submit the online application form, you will receive further instructions from ERIM Doctoral Office regarding payment options, including by bank transfer (invoice) or direct payment by credit card, iDeal.
Your spot in the course is confirmed once payment is received.
Course materials will be available via , the university鈥檚 learning management system. You can access them using the account provided upon registration. If you encounter issues, try copying the link into an incognito/private browser window.
By default, all announcements from Canvas are sent to your EUR student email account. You can add your preferred personal email address under Canvas > User Account > Settings > Ways to connect (right side menu).
If you forgot your password, please contact EUR IT Helpdesk through it.servicedesk@eur.nl.
Participation in ERIM Summer School grants you also access to Erasmus University Library. The online collection includes e-journals, e-books, online articles and other resources. It can be accessed easily through the Library website with your EUR student account.