| Project Supervisor | Shuang Zhang |
| Institution & Department | Imperial College London – Economics and Public Policy, Business School |
| Research Area | RA 4: Environment and Sustainability |
| Project Start Date | August 2026 (or by early September 2026). |
| Project Duration | 3 months |
| Application Deadline | 31/07/2026 |
| Working Pattern | Full-time (5 days per week over 3 months) |
| Working Arrangements | In person |
| How to Apply | View Guidance Here |
Project Description
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This project investigates the policies that enabled China to overcome the classic chicken-and-egg problem in electric vehicle (EV) adoption. That is, consumers are reluctant to buy EVs without a dense charging network, while firms are reluctant to build charging infrastructure when EV ownership is low. China is a remarkable exception to the global struggle with this problem, expanding its public charging network from approximately 141,000 chargers in 2016 to over 3.5 million by 2024.
The project combines a rich set of administrative datasets, covering EV charger stocks, vehicle sales, and policies, with a staggered difference-in-differences empirical strategy to identify the causal effects of different policies. Preliminary findings indicate that subsidy policies for EV charging station operators had significant positive effects on both the number of chargers and the share of EV sales.
The next phase of the project involves collecting more granular policy data, extending the car sales dataset to more recent years, analysing EV purchase subsidies as an additional policy instrument, and developing a structural model to simulate policy counterfactuals.
Internship Details
The student will be working as a member of the international research collaboration between Imperial and the University of Chicago. RA work will involve a mix of literature review, data work, econometric analysis, and academic writing. The internship can be conducted in a hybrid format combining in-person meetings at Imperial College’s South Kensington campus with remote working.
The RA will work with my research team and will contribute to the following tasks:
Academic writing support: contributing to the write-up of data sections and descriptive statistics, and preparing materials for conference presentations or working paper submission.
Data collection and cleaning: cleaning city-level data on EV charger stocks and EV sales, and collecting data on subsidy policies. This involves working with administrative data sources and government policy documents.
Empirical analysis: running and extending the staggered difference-in-differences estimations using Stata or R, implementing the de Chaisemartin et al. (2025) estimator, and producing event-study figures and regression tables.
Literature review: reviewing and summarising relevant academic literature on EV markets, network externalities, and technology adoption subsidies, to support the introduction and related literature sections of the paper.
Anticipated Benefits for the Student
The internship will give the RA substantial training and experience in:
- Working with large, real-world administrative datasets in a policy-relevant context;
- Applying state-of-the-art causal inference methods (staggered DiD);
- Contributing to a research project at the frontier of environmental and energy economics;
- Academic writing and dissemination;
- Working within an international research collaboration (Imperial College London and University of Chicago).
These skills are directly transferable to academic careers and policy-oriented research roles.
Skills, Experience and Knowledge Requirements
Essential Requirements:
- Proficiency in at least one statistical software package commonly used in economics research (Stata, R, or Python), with the ability to manage and analyse large datasets
- Familiarity with microeconometrics and causal inference methods at the PhD level (DID, IV, RD, etc.)
- Strong quantitative and analytical skills, with attention to detail in data work
Desirable Requirements:
- Reading proficiency in Mandarin Chinese would be an advantage for data collection tasks involving Chinese-language policy documents, but is not required. The supervisory team will provide support in this area.
- Interest in environmental, energy, or climate change economics
- Experience working with administrative or government data