What is the topic of this research?

This project looks at how society can steer financing towards clean technologies (cleantech), such as renewable energy, electric cars or advanced materials.

We first investigate the role of a stable and predictable policy framework to mobilise finance towards cleantech.

Trump’s recent rollback of environmental regulations makes companies less likely to invest in cleantech, as they do not know what the future holds. We aim to empirically test whether uncertainty about future environmental and climate regulations is negatively associated with investments in cleantech.

In the second part of the project, we also evaluate the role of new financing tools, such as venture capital competitions and crowdfunding platforms, on generating cleantech financing.

What is the academic interest and broader interest in general?

We use a novel approach to quantify environmental policy uncertainty, namely a text analysis of newspaper articles using machine learning algorithms.

There is a lot of academic interest for this new methodology in economics and we have recently been invited to present our results at the National Bureau of Economic Research (NBER) conference at the Massachusetts Institute of Technology (MIT) in Boston.

Regarding the broader interest, the project is part of a Swiss National Research Programme (NRP73), which aims to provide practical solutions for developing the cleantech sector in Switzerland.

We work with 10 partners from the field, ranging from business organisations, financial institutions and policy organisations, both at the Swiss and international levels.

Investors are particularly interested in our index as it can provide a quantifiable measure of policy risk.  

What are the main results so far?

We have applied the text-mining algorithm on articles in 10 US newspapers over the last 40 years and found that our index captures the history of US environmental regulations quite well, giving us confidence about the algorithm’s performance.

We identified spikes around major domestic policies, such as the enactment of the Clean Air Act in 1990 or Obama’s Green New Deal in 2009, as well as during important international climate policy events.

At this stage, we are still refining the algorithm for the policy uncertainty part.

What did you find particularly surprising or interesting?

Research has been limited in the past because of the difficulty of building quantitative indicators but it is impressive to see how much information we can now extract from newspapers using these new text-mining techniques.

We are also able to create subcategories, reflecting trends in renewable energy policy or in international climate negotiations. As news comes in daily, we can construct very detailed disaggregated datasets over several decades. This opens a lot of possibilities for future research!

Research team: Professor Joëlle Noailly (Graduate Institute), Professor Gaétan de Rassenfosse (EPFL), Laura Nowzohour (PhD candidate, Graduate Institute), Matthias van den Heuvel (PhD candidate, EPFL). www.financingcleantech.com