Using Python to apply climate change objectives of EU Taxonomy
Gurpreet Bal and Andre Chanavat’s full article can be found on the Developer Portal.
In order to meet the objectives of the European Green Deal and making Europe climate neutral by 2050; the EU is developing a series of ambitious new regulations that will not only help it achieve climate and energy goals but also aims to make the economy and health systems more resilient in the process.
For this to happen, the EU has recognized the need to change the flow of money towards sustainable activities. Which is where the EU Taxonomy comes in. At a high level this is about providing a common language and a clear definition of what sustainable is. But look under the hood and you will find a detailed classification system of environmentally sustainable economic activities and an even more detailed set of targets depending on the objective and activity.
What makes an economic activity sustainable depends on several variables; the taxonomy objective, the type of activity, the kinds of technical screening criteria companies need to pass in order to be aligned, doing no significant harm in the process and finally minimum social safeguards. It’s a data gauntlet but we’ve provided a practical example on how to measure the objectives 1 and 2.
Overall the EU taxonomy introduces six objectives to measure the portfolio exposure. These objectives are:
- Climate change mitigation
- Climate change adaptation
- The sustainable use and protection of water and marine resources
- The transition to a circular economy
- Pollution prevention and control
- The protection and restoration of biodiversity and ecosystems
In this article we will model and employ a Python script, which will use Eikon Data API to help investors measure the objective #1 & #2 of the EU taxonomy. The Python application will calculate the percentage of revenues for a portfolio, at both a portfolio level and at constituent level which are eligible or aligned with the objectives.
Underpinning the model is the Excel tool provided by TEG on the 13th March 2020. A common classification of economic activities that substantially contribute to climate change mitigation and adaptation are made available. There will be changes to this model as data providers such as ourselves, evolve our business classifications to capture new and emerging economic activities. So further alignment with other classifications and change is to be expected, but this is a useful first step. The same tool also provides details about the technical screening criteria for both activities that can make a substantial contribution to climate change mitigation and climate change adaptation. In this article and the Python sample, we are only using climate mitigation technical screening criteria.
Methodology and Implementation
At a broad level the sample application performs the following activities:
- Load the input portfolio to be analyzed
- Load the database which contain the mapping between the NAICS and TRBC and the various testing metrics
- Retrieve the segment and ESG data for the portfolio constituents from Eikon
- Massage and transpose the data to find out the exposure to climate change objective
- Generate a report
These steps are explained on the Developer Portal, so don’t hesitate to jump there to read further!
