Research Assistant (\"Pre-Doc\") - Green public finance, Crowding in, and Local growth

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Research Assistant ("Pre-Doc") - Green public finance, Crowding in, and Local growth

The London School of Economics and Political Science (LSE) is committed to building a diverse, equitable and truly inclusive university.

LSE Department of Geography and Environment

Salary from £36,513 to £41,565 per annum inclusive with potential to progress to £44,468 per annum inclusive of London allowance pro rata.

Funding is available to support this position for 12 months.

We are seeking a full time Research Assistant ("pre doc") to work closely with Professor Neil Lee on a new funded research project examining whether public green lending crowds in private capital and generates local economic growth. The project uses data on investments made by development banks to build a novel panel dataset spanning 20 years of climate relevant finance across European regions. This role is ideal for candidates planning to apply to top PhD programmes and looking for hands on research experience with original data construction and applied causal inference on high impact questions in green finance and regional development.

Key Responsibilities

• Data collection, cleaning, and merging from large scale microdata sources (e.g., patents, dissertations).
• Developing new data from textual sources.
• Conduct data analysis using econometric and statistical tools (STATA, R, or Python).
• Assist in literature reviews and summarising academic research.
• Contribute to writing academic research papers.
• Participate in meetings with collaborators and present research findings when appropriate.
• Identify and source new datasets relevant to ongoing projects.
• Support administrative and organisational aspects of the research projects, as needed.

Key Qualifications

• Undergraduate or Master's degree in Economics, Geography, Data Science or another quantitative discipline, to be completed by post start date.
• Programming skills in Python, R or STATA.
• Willingness to learn unfamiliar tools as needed (e.g. GitHub, APIs, new libraries).
• Familiarity with econometric techniques, especially panel data methods and difference in differences methods.
• Clear, concise written and verbal communication skills.
• Ability to work independently and manage time across multiple research tasks.

We offer an occupational pension scheme, generous annual leave and excellent training and development opportunities.

The expected start date is September 2026, subject to negotiation. The appointment will be for 12 months.